Rice Genome Engineering and Gene Editing: Methods and Protocols (Methods in Molecular Biology, 2238) 1071610678, 9781071610671

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Methods in Molecular Biology 2238

Anindya Bandyopadhyay Roger Thilmony Editors

Rice Genome Engineering and Gene Editing Methods and Protocols

METHODS

IN

MOLECULAR BIOLOGY

Series Editor John M. Walker School of Life and Medical Sciences University of Hertfordshire Hatfield, Hertfordshire, UK

For further volumes: http://www.springer.com/series/7651

For over 35 years, biological scientists have come to rely on the research protocols and methodologies in the critically acclaimed Methods in Molecular Biology series. The series was the first to introduce the step-by-step protocols approach that has become the standard in all biomedical protocol publishing. Each protocol is provided in readily-reproducible step-bystep fashion, opening with an introductory overview, a list of the materials and reagents needed to complete the experiment, and followed by a detailed procedure that is supported with a helpful notes section offering tips and tricks of the trade as well as troubleshooting advice. These hallmark features were introduced by series editor Dr. John Walker and constitute the key ingredient in each and every volume of the Methods in Molecular Biology series. Tested and trusted, comprehensive and reliable, all protocols from the series are indexed in PubMed.

Rice Genome Engineering and Gene Editing Methods and Protocols

Edited by

Anindya Bandyopadhyay Synthetic Biology, Biofuel and Genome Editing R&D, Reliance Industries Ltd, Navi Mumbai, Maharashtra, India

Roger Thilmony Crop Improvement and Genetics Research Unit, USDA-ARS, Albany, CA, USA

Editors Anindya Bandyopadhyay Synthetic Biology, Biofuel and Genome Editing R&D Reliance Industries Ltd Navi Mumbai, Maharashtra, India

Roger Thilmony Crop Improvement and Genetics Research Unit USDA-ARS Albany, CA, USA

ISSN 1064-3745 ISSN 1940-6029 (electronic) Methods in Molecular Biology ISBN 978-1-0716-1067-1 ISBN 978-1-0716-1068-8 (eBook) https://doi.org/10.1007/978-1-0716-1068-8 © Springer Science+Business Media, LLC, part of Springer Nature 2021 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Humana imprint is published by the registered company Springer Science+Business Media, LLC, part of Springer Nature. The registered company address is: 1 New York Plaza, New York, NY 10004, U.S.A.

Preface Rice is one of the most important crops and is a staple food for more than two-thirds of the world population. This makes the stability of rice production crucially important for our economic and social development. However, like any crop, its production is challenged by biotic and abiotic stress factors like bacteria, viruses, fungi, insect pests, weeds, drought, flood, extreme temperatures, and saline soils. In the past 60 years, innovation in science and technology has been able to successfully increase rice yield from an average of 2 tons/ hectare (t/h) in 1960 to an average of 4 t/h in 2000 with peak production reaching 6–10 t/ h in some areas. This is the result of modern agricultural practices including irrigation, fertilizers, and improved pest and weed control, but also the introduction of high-yielding varieties, beginning with the “green revolution” cultivar IR8 in 1966 developed by the International Rice Research Institute. Since then, numerous additional high-yielding and stress-resilient varieties have been introduced, having a dramatic positive impact on rice production. The enhanced varieties were developed by innovative breeding programs using an array of different approaches to improve rice with a myriad of beneficial traits. In the last 30 years, molecular approaches have been added to the toolbox and are being utilized for the continued development of rice with enhanced traits. Most recently, CRISPR gene editing systems and other genome engineering tools have been developed to further enable the sophisticated and precise modification of the rice genome for crop improvement. With the ever-increasing world population, these tools provide much needed approaches for further increasing our ability to improve rice and other crops to feed our hungry world. This Methods in Molecular Biology volume documents rice molecular biology, genetic engineering, and genome editing technologies. The book is divided into three topic areas. The first part focuses on genetic engineering and tissue culture of rice, including efficient methods for rice transformation and regeneration, as well as two systems that enable the efficient stacking together of multiple transgenic traits. The second part covers multiple chapters on genome editing and targeted integration in rice including multiple methods utilizing CRISPR systems for targeted gene knock-out or genome modification via base editing, as well as the use of homologous recombination and site-specific recombination to perform targeted gene integration within the rice genome. Finally, the last part includes diverse methods describing bioinformatic, molecular, and cellular analyses in rice. We hope that this collection of methods will be a useful resource to researchers worldwide and further their efforts on advancing research and producing genetically improved rice varieties. Maharashtra, India Albany, CA, USA

Anindya Bandyopadhyay Roger Thilmony

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Contents Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contributors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

PART I

GENETIC ENGINEERING AND TISSUE CULTURE OF RICE

1 Gene Assembly in Agrobacterium via Nucleic Acid Transfer Using Recombinase Technology (GAANTRY) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Leyla T. Hathwaik, James G. Thomson, and Roger Thilmony 2 TransGene Stacking II Vector System for Plant Metabolic Engineering and Synthetic Biology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Qinlong Zhu and Yao-Guang Liu 3 Morphogenic Regulators and Their Application in Improving Plant Transformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Samson Nalapalli, Meral Tunc-Ozdemir, Yuejin Sun, Sivamani Elumalai, and Qiudeng Que 4 A Rapid Method for Stably Transforming Rice Seeds . . . . . . . . . . . . . . . . . . . . . . . . Sudheer Kumar and Neeti Sanan-Mishra 5 Agrobacterium tumefaciens-Mediated Transformation of Rice by Hygromycin Phosphotransferase (hptII) Gene Containing CRISPR/Cas9 Vector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shuvobrata Majumder, Karabi Datta, and Swapan Kumar Datta 6 Genotype-Independent Regeneration and Transformation Protocol for Rice Cultivars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tanushri Kaul, Sonia Khan Sony, Nitya Meenakshi Raman, Khaled Fathy Abdel Motelb, and Jyotsna Bharti

PART II

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GENOME EDITING AND TARGETED INTEGRATION IN RICE

7 Rapid Vector Construction and Assessment of BE3 and Target-AID C to T Base Editing Systems in Rice Protoplasts . . . . . . . . . . . . . . . . . 95 Simon Sretenovic, Changtian Pan, Xu Tang, Yong Zhang, and Yiping Qi 8 Genome Editing of Rice by CRISPR-Cas: End-to-End Pipeline for Crop Improvement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Amit Das, Pallavi Ghana, Bhojaraja Rudrappa, Rita Gandhi, Venkata Sresty Tavva, and Amitabh Mohanty 9 Single Base Editing Using Cytidine Deaminase to Change Grain Size and Seed Coat Color in Rice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 My Vo Thi Tra, Xiaojia Yin, Ishita Bajal, Christian Paolo Balahadia, William Paul Quick, and Anindya Bandyopadhyay

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Contents

Analysis of Off-Target Mutations in CRISPR-Edited Rice Plants Using Whole-Genome Sequencing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Guanqing Liu, Yiping Qi, and Tao Zhang Efficient Genome Editing in Rice Protoplasts Using CRISPR/CAS9 Construct . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Martine Bes, Leo Herbert, Thibault Mounier, Anne-Ce´cile Meunier, Franz Durandet, Emmanuel Guiderdoni, and Christophe Pe´rin Single Transcript Unit CRISPR 2.0 Systems for Genome Editing in Rice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xu Tang, Yiping Qi, and Yong Zhang Improving a Quantitative Trait in Rice by Multigene Editing with CRISPR-Cas9 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yesuf Teslim Yimam, Jianping Zhou, Sayed Abdul Akher, Xuelian Zheng, Yiping Qi, and Yong Zhang Rice Haploid Inducer Development by Genome Editing . . . . . . . . . . . . . . . . . . . . Juntao Liu, Dawei Liang, Li Yao, Ya Zhang, Chunxia Liu, Yubo Liu, Yanli Wang, Hongju Zhou, Timothy Kelliher, Xingping Zhang, and Anindya Bandyopadhyay FLP-Mediated Site-Specific Gene Integration in Rice. . . . . . . . . . . . . . . . . . . . . . . . Vibha Srivastava Rice Gene Targeting by Homologous Recombination with Positive-Negative Selection Strategy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rie Terada and Zenpei Shimatani

PART III 17

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BIOINFORMATICS, CELLULAR, AND MOLECULAR ANALYSIS OF RICE

Prediction of Rice Transcription Start Sites Using TransPrise: A Novel Machine Learning Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Stepan Pachganov, Khalimat Murtazalieva, Alexei Zarubin, Tatiana Taran, Duane Chartier, and Tatiana V. Tatarinova Single Cell Type Specific RNA Isolation and Gene Expression Analysis in Rice Using Laser Capture Microdissection (LCM)-Based Method. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vibhav Gautam, Sourav Chatterjee, and Ananda K. Sarkar Immunolocalization Analysis of C4 Proteins in the Leaf Tissue of Rice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ˜ onuevo, Hsiang-Chun Lin, Joanne Jerenice An William Paul Quick, and Anindya Bandyopadhyay Selection of Suitable Reference Genes for qRT-PCR Gene Expression Studies in Rice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Meng Wang and Navreet K. Bhullar Rice Protoplast Isolation and Transfection for Transient Gene Expression Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jennylyn L. Trinidad, Toshisangba Longkumer, and Ajay Kohli

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Identification and Downstream Analyses of Domains Amplified in Plant Genomes: The Case of StAR-Related Lipid Transfer (START) Domains in Rice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325 Sanjeet Kumar Mahtha, Ravi Kiran Purama, Renu Kumari, and Gitanjali Yadav Assessing Rice Salinity Tolerance: From Phenomics to Association Mapping. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339 Nadia Al-Tamimi, Helena Oakey, Mark Tester, ˜o and S
o nia Negra

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

377

Contributors SAYED ABDUL AKHER • Department of Biotechnology, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China NADIA AL-TAMIMI • Division of Biological and Environmental Sciences and Engineering (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia JOANNE JERENICE AN˜ONUEVO • International Rice Research Institute, Los Bano˜s, Philippines a t, Berlin, Germany; ISHITA BAJAL • Dahlem Center of Plant Sciences Freie Universit€ Syngenta Beijing Innovation Center, Beijing, China CHRISTIAN PAOLO BALAHADIA • International Rice Research Institute, Manila, Philippines ANINDYA BANDYOPADHYAY • Syngenta Beijing Innovation Center, ZhongGuanCun Life Science Park, Beijing, China; International Rice Research Institute, Los Bano˜s, Philippines; Synthetic Biology Department, Reliance Industries Limited, RCP, NaviMumbai, India MARTINE BES • CIRAD, UMR AGAP, Montpellier Cedex 5, France; Universite´ de Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, France JYOTSNA BHARTI • Plant Biology and Biotechnology Division, Nutritional Improvement of Crops, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India NAVREET K. BHULLAR • Department of Biology, ETH Zurich (Swiss Federal Institute of Technology), Zurich, Switzerland DUANE CHARTIER • International Center for Art Intelligence, Inc, Los Angeles, CA, USA SOURAV CHATTERJEE • National Institute of Plant Genome Research (NIPGR), New Delhi, India AMIT DAS • Formerly at Corteva Agriscience™, DuPont Knowledge Centre, Hyderabad, Telangana, India KARABI DATTA • Laboratory of Translational Research on Transgenic Crops, University of Calcutta, Kolkata, India SWAPAN KUMAR DATTA • Laboratory of Translational Research on Transgenic Crops, University of Calcutta, Kolkata, India FRANZ DURANDET • IAGE Company, Montpellier Cedex 5, France SIVAMANI ELUMALAI • Seeds Research, Syngenta Crop Protection LLC, Research Triangle Park, NC, USA RITA GANDHI • Formerly at Corteva Agriscience™, DuPont Knowledge Centre, Hyderabad, Telangana, India VIBHAV GAUTAM • National Institute of Plant Genome Research (NIPGR), New Delhi, India PALLAVI GHANA • Formerly at Corteva Agriscience™, DuPont Knowledge Centre, Hyderabad, Telangana, India EMMANUEL GUIDERDONI • CIRAD, UMR AGAP, Montpellier Cedex 5, France; Universite´ de Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, France

xi

xii

Contributors

LEYLA T. HATHWAIK • United States Department of Agriculture—Agriculture Research Service, Western Regional Research Center, Crop Improvement and Genetics Research Unit, Albany, CA, USA LEO HERBERT • CIRAD, UMR AGAP, Montpellier Cedex 5, France; Universite´ de Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, France TANUSHRI KAUL • Plant Biology and Biotechnology Division, Nutritional Improvement of Crops, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India TIMOTHY KELLIHER • Syngenta Beijing Innovation Center, ZhongGuanCun Life Science Park, Beijing, China AJAY KOHLI • Strategic Innovation Platform, International Rice Research Institute, Manila, Philippines SUDHEER KUMAR • Plant RNAi Biology Group, International Centre for Genetic Engineering and Biotechnology, New Delhi, India RENU KUMARI • National Institute of Plant Genome Research (NIPGR), New Delhi, India DAWEI LIANG • Syngenta Beijing Innovation Center, ZhongGuanCun Life Science Park, Beijing, China HSIANG-CHUN LIN • International Rice Research Institute, Los Bano˜s, Philippines CHUNXIA LIU • Syngenta Beijing Innovation Center, ZhongGuanCun Life Science Park, Beijing, China GUANQING LIU • Jiangsu Key Laboratory of Crop Genetics and Physiology, Jiangsu CoInnovation Center for Modern Production Technology of Grain Crops, Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, Jiangsu, China; Key Laboratory of Plant Functional Genomics of the Ministry of Education, Joint International Research Laboratory of Agriculture and AgriProduct Safety of the Ministry of Education, Yangzhou University, Yangzhou, Jiangsu, China JUNTAO LIU • Syngenta Beijing Innovation Center, ZhongGuanCun Life Science Park, Beijing, China YAO-GUANG LIU • State Key Laboratory for Conservation and Utilization of Subtropical Agro Bioresources, South China Agricultural University, Guangzhou, China YUBO LIU • Syngenta Beijing Innovation Center, ZhongGuanCun Life Science Park, Beijing, China TOSHISANGBA LONGKUMER • Strategic Innovation Platform, International Rice Research Institute, Manila, Philippines; Institute of Plant and Microbial Biology, Academia Sinica, Taipei, Taiwan SANJEET KUMAR MAHTHA • National Institute of Plant Genome Research (NIPGR), New Delhi, India SHUVOBRATA MAJUMDER • Laboratory of Translational Research on Transgenic Crops, University of Calcutta, Kolkata, India ANNE-CE´CILE MEUNIER • CIRAD, UMR AGAP, Montpellier Cedex 5, France; Universite´ de Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, France AMITABH MOHANTY • Formerly at Corteva Agriscience™, DuPont Knowledge Centre, Hyderabad, Telangana, India; Corteva Agriscience, Johnston, IA, USA

Contributors

xiii

KHALED FATHY ABDEL MOTELB • Plant Biology and Biotechnology Division, Nutritional Improvement of Crops, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India THIBAULT MOUNIER • CIRAD, UMR AGAP, Montpellier Cedex 5, France; Universite´ de Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, France KHALIMAT MURTAZALIEVA • Vavilov Institute of General Genetics, Moscow, Russia SAMSON NALAPALLI • Seeds Research, Syngenta Crop Protection LLC, Research Triangle Park, NC, USA SO´NIA NEGRA˜O • School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland HELENA OAKEY • School of Agriculture Food and Wine, University of Adelaide, Urrbrae, SA, Australia STEPAN PACHGANOV • Ugra Research Institute of Information Technologies, KhantyMansiysk, Russia CHANGTIAN PAN • Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD, USA CHRISTOPHE PE´RIN • CIRAD, UMR AGAP, Montpellier Cedex 5, France; Universite´ de Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, France RAVI KIRAN PURAMA • National Institute of Plant Genome Research (NIPGR), New Delhi, India YIPING QI • Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD, USA; Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, MD, USA QIUDENG QUE • Seeds Research, Syngenta Crop Protection LLC, Research Triangle Park, NC, USA WILLIAM PAUL QUICK • International Rice Research Institute, Los Bano˜s, Philippines NITYA MEENAKSHI RAMAN • Plant Biology and Biotechnology Division, Nutritional Improvement of Crops, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India BHOJARAJA RUDRAPPA • Formerly at Corteva Agriscience™, DuPont Knowledge Centre, Hyderabad, Telangana, India NEETI SANAN-MISHRA • Plant RNAi Biology Group, International Centre for Genetic Engineering and Biotechnology, New Delhi, India ANANDA K. SARKAR • National Institute of Plant Genome Research (NIPGR), New Delhi, India ZENPEI SHIMATANI • Graduate School of Science, Technology and Innovation, Kobe University, Kobe, Hyogo, Japan SONIA KHAN SONY • Plant Biology and Biotechnology Division, Nutritional Improvement of Crops, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India VENKATA SRESTY TAVVA • Formerly at Corteva Agriscience™, DuPont Knowledge Centre, Hyderabad, Telangana, India SIMON SRETENOVIC • Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD, USA

xiv

Contributors

VIBHA SRIVASTAVA • Department of Crop, Soil and Environmental Sciences, University of Arkansas, Fayetteville, AR, USA; Department of Horticulture, University of Arkansas, Fayetteville, AR, USA YUEJIN SUN • Seeds Research, Syngenta Crop Protection LLC, Research Triangle Park, NC, USA XU TANG • Department of Biotechnology, Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China TATIANA TARAN • Odessa National University, Odessa, Ukraine TATIANA V. TATARINOVA • Vavilov Institute of General Genetics, Moscow, Russia; Department of Biology, University of La Verne, La Verne, CA, USA; A.A. Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russia; Siberian Federal University, Krasnoyarsk, Russia RIE TERADA • Graduate School of Agriculture, Meijo University, Nagoya, Aichi, Japan MARK TESTER • Division of Biological and Environmental Sciences and Engineering (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia ROGER THILMONY • United States Department of Agriculture—Agriculture Research Service, Western Regional Research Center, Crop Improvement and Genetics Research Unit, Albany, CA, USA JAMES G. THOMSON • United States Department of Agriculture—Agriculture Research Service, Western Regional Research Center, Crop Improvement and Genetics Research Unit, Albany, CA, USA MY VO THI TRA • International Rice Research Institute, Manila, Philippines JENNYLYN L. TRINIDAD • Strategic Innovation Platform, International Rice Research Institute, Manila, Philippines MERAL TUNC-OZDEMIR • Metabolon, Inc., Morrisville, NC, USA MENG WANG • Department of Biology, ETH Zurich (Swiss Federal Institute of Technology), Zurich, Switzerland; School of Life Sciences, University of Science and Technology of China, Hefei, China YANLI WANG • Syngenta Beijing Innovation Center, ZhongGuanCun Life Science Park, Beijing, China GITANJALI YADAV • National Institute of Plant Genome Research (NIPGR), New Delhi, India; Department of Plant Sciences, University of Cambridge, Cambridge, UK LI YAO • Syngenta Beijing Innovation Center, ZhongGuanCun Life Science Park, Beijing, China YESUF TESLIM YIMAM • Department of Biotechnology, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China XIAOJIA YIN • International Rice Research Institute, Manila, Philippines ALEXEI ZARUBIN • Tomsk National Research Medical Center of the Russian Academy of Sciences, Research Institute of Medical Genetics, Tomsk, Russia TAO ZHANG • Jiangsu Key Laboratory of Crop Genetics and Physiology, Jiangsu CoInnovation Center for Modern Production Technology of Grain Crops, Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, Jiangsu, China; Key Laboratory of Plant Functional Genomics of the Ministry of Education, Joint International Research Laboratory of Agriculture and AgriProduct Safety of the Ministry of Education, Yangzhou University, Yangzhou, Jiangsu, China

Contributors

xv

XINGPING ZHANG • Syngenta Beijing Innovation Center, ZhongGuanCun Life Science Park, Beijing, China YA ZHANG • Syngenta Beijing Innovation Center, ZhongGuanCun Life Science Park, Beijing, China YONG ZHANG • Department of Biotechnology, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China XUELIAN ZHENG • Department of Biotechnology, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China HONGJU ZHOU • Syngenta Beijing Innovation Center, ZhongGuanCun Life Science Park, Beijing, China JIANPING ZHOU • Department of Biotechnology, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China QINLONG ZHU • State Key Laboratory for Conservation and Utilization of Subtropical Agro Bioresources, South China Agricultural University, Guangzhou, China

Part I Genetic Engineering and Tissue Culture of Rice

Chapter 1 Gene Assembly in Agrobacterium via Nucleic Acid Transfer Using Recombinase Technology (GAANTRY) Leyla T. Hathwaik, James G. Thomson, and Roger Thilmony Abstract Plant biotechnology provides a means for the rapid genetic improvement of crops including the enhancement of complex traits like yield and nutritional quality through the introduction and coordinated expression of multiple genes. GAANTRY (gene assembly in Agrobacterium by nucleic acid transfer using recombinase technology) is a flexible and effective system for stably stacking multiple genes within an Agrobacterium virulence plasmid transfer DNA (T-DNA) region. The system provides a simple and efficient method for assembling and stably maintaining large stacked constructs within the GAANTRY ArPORT1 Agrobacterium rhizogenes strain. The assembly process utilizes unidirectional site-specific recombinases in vivo and an alternating bacterial selection scheme to sequentially assemble multiple genes into a single transformation construct. A detailed description of the procedures used for bacterial transformation, selection, counter selection, and genomic PCR validation with the GAANTRY system are presented. The methods described facilitate the efficient assembly and validation of large GAANTRY T-DNA constructs. This powerful, yet simple to use, technology will be a convenient tool for transgene stacking and plant genetic engineering of rice and other crop plants. Key words Plant biotechnology, Transformation, Agrobacterium rhizogenes, Transfer DNA (T-DNA), Transgene assembly, Site-specific recombination, Gene stacking, Virulence plasmid, Genetic engineering

1

Introduction Plant research has utilized Agrobacterium-mediated plant transformation as a means of plant genetic engineering for more than 30 years [1, 2]. In most instances one or a few genes are introduced into the plant genome, but recently the assembly of large transformation constructs that carry multiple genes has been desired. Unfortunately, it is typically challenging to construct and efficiently transform plants with large constructs carrying five or more genes. Since the in vitro manipulation of large constructs can be difficult and/or inefficient to perform using traditional cloning techniques, a variety of alternative approaches have been developed for stacking

Anindya Bandyopadhyay and Roger Thilmony (eds.), Rice Genome Engineering and Gene Editing: Methods and Protocols, Methods in Molecular Biology, vol. 2238, https://doi.org/10.1007/978-1-0716-1068-8_1, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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multiple genes together. Strategies employing rare-cutting homing endonucleases, commercial cloning systems (i.e., multisite Gateway), Gibson assembly, type IIS restriction enzymes, homologous recombination in yeast, the Cre site-specific recombinase, as well as combinations of these methods have been developed [3– 13]. Although these efforts have been shown to successfully produce large and complex constructs, these systems all utilize either a binary vector plasmid or a binary bacterial artificial chromosome plasmid vector as the transformation construct and have frequently exhibited inefficient assembly processes and/or instability problems in E. coli or Agrobacterium. Also, relatively few of these approaches have been shown to develop large stacked constructs that efficiently generate low copy, high-quality stable transgenic plants with all of the expected functional phenotypes. Recently, we designed and constructed the gene assembly in Agrobacterium via nucleic acid transfer using recombinase technology (GAANTRY) system and demonstrated its capacity to sequentially stacking ten cargo sequences within the virulence plasmid T-DNA of the Agrobacterium rhizogenes strain ArPORT1 (Fig. 1) [14]. The GAANTRY assembly process utilizes three unidirectional site-specific recombinases in vivo and an alternating bacterial selection scheme to iteratively build multiple genes into a transfer DNA (T-DNA). Below we provide a detailed description for a simplified protocol for GAANTRY assembly and strain validation. This powerful, yet simple to use, transgene stacking technology will be a valuable tool for plant genetic engineering of rice and other crop plants.

2

Materials

2.1 The GAANTRY System

The GAANTRY system requires only a recipient Agrobacterium strain and four plasmid vectors for construct assembly [14]. 1. The ArPORT1 bacterial strain is a kanamycin-resistant Agrobacterium rhizogenes GAANTRY recipient strain. It is a disarmed strain (where the native T-DNA has been removed from the pRi virulence plasmid) and is recA making it deficient in homologous recombination. The recA gene was inactivated using a tetracycline resistance marker and homologous recombination. Although the strain is resistant to 5 mg/L tetracycline, the antibiotic is not typically used for selection. The strain contains a 320 base pair (bp) sequence of the left border region of Agrobacterium tumefaciens strain C58 (including the 25 bp LB direct repeat), the 56 bp A118 attP recognition site, the nptIII gene conferring bacterial kanamycin resistance, and the 106 bp ParA single multimer resolution site (MRS) in place of the native T-DNA (Fig. 2).

GAANTRY Gene Stacking

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Fig. 1 Diagram depicting GAANTRY-mediated stacking of cargo sequences into the A. rhizogenes ArPORT1 virulence plasmid T-DNA. The sequential assembly process occurs iteratively, incorporating cargo sequences from an alternating series of B and P Donor vectors via electroporation with the appropriate B or P Helper vector (not shown) and bacterial antibiotic selection. The A. rhizogenes ArPORT1 pRi virulence plasmid is shown carrying eight cargo sequences inserted between the left border (LB) and right border (RB) T-DNA repeats

2. Plasmid vectors: (a) The B and P “Donor” vectors carry attB (or attP) recombinase recognition sites respectively. In short, the A118 and TP901-1 recombinase recognition sites flank a cloning region in each plasmid where cargo sequence(s) of interest can be inserted. The cloning region includes a large number of unique restriction recognition sites for traditional restriction enzyme-based cloning of sequences of interest. The donor plasmids also contain a kanamycin or gentamicin bacterial resistance marker, respectively, as well as the sacB negative selection marker (conferring sucrose sensitivity) and a ParA MRS recognition sequence. Diagrams of the B and P Donor plasmids are shown in Fig. 2. The complete annotated plasmid sequences for the B Donor (MG687272) and P Donor (MG687284) plasmids are available from GenBank. Note, Donor vectors

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Fig. 2 Linear maps of the ArPORT1 recipient region and the B and P Donor vectors. The A. rhizogenes ArPORT1 recipient region with a T-DNA left border region, an A118 attP recognition site, a bacterial kanamycin resistance gene, and the ParA MRS recognition site inserted in place of the native A. rhizogenes T-DNA is shown on top. Maps of the B and P Donor sequences showing the large multiple cloning sites where sequences of interest can be inserted, flanked by either attB or attP recombinase recognition sites, are also shown. The plasmid vectors carry either the GmR (bacterial gentamicin resistance gene) or the KanR (bacterial kanamycin resistance gene) selection markers. Both plasmids also contain the levansucrase gene conferring bacterial sensitivity to sucrose (sacB), the ColE1 plasmid origin of replication (ori), and bacterial ampicillin resistance gene (AmpR)

that enable Gateway or Golden Gate cloning of cargo sequences are also available [14]. (b) The B and P “Helper” plasmids confer ampicillin resistance in E. coli and carry an operon expressing either the A118 and ParA or the TP901-1 and ParA recombinase enzymes, respectively. The annotated plasmid sequences for the B and P Helper vectors are available from GenBank (MG687274, MG687275).

GAANTRY Gene Stacking

2.2 Growth Medium, Culture Conditions, and Equipment

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1. Low-salt Luria-Bertani (LB) medium: 10 g/L Bacto Tryptone, 5 g/L yeast extract, and 5 g/L NaCl. Adjust pH to 7.5 with sodium hydroxide (NaOH) and sterilize by autoclaving. For LB solid medium add 10 g of Bacto agar prior to autoclaving. Supplement LB medium with appropriate antibiotics for plasmid selection in E. coli and strain selection in Agrobacterium (see item 3). 2. LB solid medium with 5% (w/v) sucrose: LB medium (as described above) with 50 g/L sucrose added and the appropriate antibiotic. 3. Antibiotics gentamicin, kanamycin, and carbenicillin. For plasmid selection in E. coli, 10 mg/L gentamicin is used, while 100 mg/L gentamicin is for selecting GAANTRY Agrobacterium ArPORT1 strains. For both E. coli and Agrobacterium, 50 mg/L kanamycin is used for selection. Carbenicillin at 100 mg/L is the concentration used for selecting the helper plasmids in E. coli. 4. Incubator/shaker at 30 and 37
C. 5. Eppendorf ThermoMixer. 6. Microcentrifuge. 7. Electroporation cuvettes (2 mm gap). 8. Gene Pulser electroporation apparatus. 9. PCR thermocycler. 10. Agarose gel electrophoresis apparatus.

3

Methods

3.1 Preparation of Donor and Helper Plasmids

1. To insert cargo DNA sequences within the Donor plasmids, manipulate P and B Donor vectors using standard cloning and E. coli microbiological techniques [15]. 2. To prepare the plasmids, streak desired clones for single colony selection from a 80
C glycerol stock onto LB plates with the appropriate antibiotic selection. 3. Transfer a single colony to 5 ml of LB liquid broth with appropriate selection in a 15 ml snap-cap tube and incubate overnight at 37
C under continuous shaking (250 rpm). 4. Harvest the cells by centrifugation at 10,000  g and follow a protocol of choice for mini plasmid preparation (e.g., the Zymo Research ZR Plasmid Miniprep protocol or a similar product from other vendors) (see Note 1). Prior to use, dilute the Donor and Helper plasmids in water to a 50 ng/μl concentration.

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3.2 Preparation of the Electrocompetent ArPORT1 Recipient Strain

Electrocompetent GAANTRY Agrobacterium rhizogenes ArPORT1 cells are prepared at room temperature according to Tu and colleagues with minor modifications (see Note 2) [16]. 1. To prepare the electrocompetent cells, streak GAANTRY A. rhizogenes ArPORT1 recipient strain on LB medium to produce individual isolated colonies. Antibiotic selection will depend on the desired recipient strain. For the original strain or strains carrying two or other even numbered stacks of cargo, the antibiotic selection will be 50 mg/L kanamycin. Alternatively, if the desired strain contains odd numbered stacks of cargo, the appropriate selection will be 100 mg/L gentamicin. 2. Transfer a single colony to 5 ml LB medium with suitable selection in a 15 ml snap-cap tube and incubate at 30
C under continuous shaking (250 rpm) for 16–18 h (OD600 > 1.5). 3. Dilute the overnight culture by adding 150 μl of culture to 1.35 ml of nonselective LB medium in a 1.5 ml microcentrifuge tube. Make four tubes per transformation. 4. Place tubes in an Eppendorf ThermoMixer at 30
C and 900 rpm for 3–4 h until the density reaches OD600 ¼ 0.4–0.6 (see Note 3). 5. When the desired optical density is reached, centrifuge the cells at 1000  g for 5 min at room temperature. 6. Discard the supernatant and gently resuspend the cells in 100 μl of sterile water. Combine the four tubes. The cultures are kept at room temperature and all the procedures are performed at room temperature (~22–24
C) from this point on. 7. Add 1 ml of sterile water to the combined cell suspension. 8. Centrifuge at 1000  g for 5 min, and then pour off the supernatant. 9. Wash the cells one more time by repeating steps 7 and 8. 10. Resuspend cells in 50 μl of sterile water and use for immediate electroporation (see Note 4).

3.3 Loading B Donor Cargo into the ArPORT1 Strain

Perform all steps at room temperature unless stated otherwise. A general diagram of the procedure is shown in Fig. 3. 1. Prepare a solution with 2 μl (50 ng/μl) of B Donor and 2 μl (50 ng/μl) of B Helper plasmid DNA. This solution needs to be low in dissolved ions (i.e., the DNA is dissolved in water or plasmid elution buffer), so it does not cause an arcing during electroporation (see Note 5).

GAANTRY Gene Stacking

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Fig. 3 A diagram of the basic microbiological screening procedure used for GAANTRY assembly of even numbered cargos is shown. The process is similarly repeated for odd numbered cargos with the P Donor and P Helper plasmids and kanamycin selection

2. Add B Helper and B Donor plasmid solution to a room temperature 50 μl aliquot of electrocompetent ArPORT1 cells. 3. Thoroughly mix the plasmid DNA and the cells by pipetting up and down.

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4. Transfer the cell-plasmid mixture into a 2 mm gap electroporation cuvette. Flick the cuvette gently to mix and tap on the table to remove any air bubbles. 5. Insert the electroporation cuvette containing the cells and the plasmid solution in to a Gene Pulser electroporation apparatus (or similar equipment) and electroporate at 25 μF capacitance, 400 Ω resistance, and 2.4 kV. Note, 1 mm gap cuvettes can also be used, but the voltage should be adjusted to 1.8 kV. 6. Remove the cuvette from the electroporation apparatus and immediately pipet 1 ml of nonselective LB broth into the cuvette to suspend the bacteria. 7. Gently pipette up and down to mix the cells with the LB medium and then transfer culture into a sterile 1.5 ml microcentrifuge tube. 8. Place the tube containing the culture in a shaking (100–120 rpm) 30
C incubator. 9. Allow cells to recover and grow for 90 min. 10. Pellet cells by centrifugation at 1000  g for 2 min. 11. Remove 900 μl of supernatant and then resuspend the pellet in the remaining LB broth. 12. Plate resuspended cells on solid LB medium supplemented with 100 mg/L gentamicin. 13. Place in a 30
C incubator for 38–44 h to produce gentamicinresistant colonies. 14. Select an individual colony and streak to attain isolated colonies on a LB plate supplemented with 100 mg/L gentamicin and 5% weight/volume (w/v) sucrose (see Note 6). 15. Incubate plate for 38–44 h at 30
C. 16. Select an individual gentamicin-resistant, sucrose-insensitive colony from the sucrose selection plate to generate replicate plates and a liquid culture in the order below: (a) Use a sterile pipette tip to pick a colony and streak the bacteria on solid LB medium containing 50 mg/L kanamycin. (The lack of growth will confirm excision and purity.) (b) Using the same tip, streak bacteria on solid LB medium with 100 mg/L gentamicin and 5% w/v sucrose. (The presence of growth reconfirms integration of cargo and the excision of sacB.) (c) Then place the tip with bacteria from the selected colony in 5 mL of liquid LB medium with 100 mg/L gentamicin. (This culture will be used to archive the strain as a 80
C glycerol stock for later use in plant transformation or for additional rounds of stacking.)

GAANTRY Gene Stacking

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17. Incubate plates for 38–44 h at 30
C and then score for growth (see Note 7). 18. Incubate 5 mL culture by shaking at 250 rpm at 30
C for overnight (OD600 > 1.5). 19. Resample the confirmed colony from step 16 to extract genomic DNA (see Subheading 3.5). 20. Once the strain is microbiologically confirmed and genomic PCR confirms the presence of the added cargo, archive the strain as a 80
C glycerol stock and/or make electrocompetent cells for the insertion of additional cargo with a P Donor and P Helper plasmid (see Subheadings 3.2 and 3.4). 3.4 Loading P Donor Cargo into the ArPORT1 Strain

Perform all steps at room temperature unless stated otherwise. 1. Prepare a solution with 2 μl (50 ng/μl) of P Donor and 2 μl (50 ng/μl) of P Helper plasmid DNA (see Note 5). 2. Add P Helper and P Donor plasmid solution to a room temperature 50 μl aliquot of electrocompetent ArPORT1 cells. 3. Thoroughly mix the plasmid DNA and the cells by pipetting up and down. 4. Transfer the cell-plasmid mixture into a 2 mm gap electroporation cuvette. Flick the cuvette gently to mix and tap on the table to remove any air bubbles. 5. Insert the electroporation cuvette containing the cells and the plasmid solution into a Gene Pulser electroporation apparatus (or similar equipment) and electroporate at 25 μF capacitance, 400 Ω resistance, and 2.4 kV. Note, 1 mm gap cuvettes can also be used, but the voltage should be adjusted to 1.8 kV. 6. Remove cuvette from the electroporation apparatus and immediately pipet 1 mL of nonselective LB broth into the cuvette to suspend the bacteria. 7. Gently pipette up and down to mix the cells with the LB medium and then transfer culture into a sterile 1.5 mL microcentrifuge tube. 8. Place the tube containing the culture in a shaking (100–120 rpm) 30
C incubator. 9. Allow cells to recover and grow for 90 min. 10. Pellet cells by centrifugation at 1000  g for 2 min. 11. Remove 900 μl supernatant and resuspend pellet in remaining LB broth. 12. Plate resuspended cells on solid LB medium supplemented with 50 mg/L kanamycin. 13. Place in a 30
C incubator for 38–44 h to produce kanamycinresistant colonies.

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14. Select an individual colony and streak to attain isolated colonies on a LB plate supplemented with 50 mg/L kanamycin and 5% (w/v) sucrose (see Note 6). 15. Select an individual kanamycin-resistant, sucrose-insensitive colony from the sucrose purification plate to produce replicate plates and a liquid culture in the order below: (a) Use a sterile pipette tip to pick a colony and streak the bacteria on solid LB medium with 100 mg/L gentamicin. (The lack of growth will confirm excision and purity.) (b) Using the same tip, streak bacteria on solid LB medium with 50 mg/L kanamycin and 5% w/v sucrose. (The presence of growth reconfirms integration of cargo and the excision of sacB.) (c) Then place the tip with bacteria from the selected colony in 5 mL of liquid LB medium with 50 mg/L kanamycin. (This culture will be used to archive the strain as a 80
C glycerol stock for later use in plant transformation or for additional rounds of stacking.) 16. Incubate plates for 38–44 h at 30
C and then score for growth (see Note 7). 17. Incubate 5 mL culture by shaking at 250 rpm at 30
C for overnight (OD600 > 1.5). 18. Resample the confirmed colony from step 16 to extract genomic DNA (see Subheading 3.5). 19. Once the strain is microbiologically confirmed and genomic PCR confirms the presence of the added cargo, archive the strain as a 80
C glycerol stock and/or make electrocompetent cells for the insertion of additional cargo with a B Donor and B Helper plasmid (see Subheadings 3.2 and 3.3). 3.5 Quick Genomic DNA Extraction for ArPORT1 Colonies

1. Resample the colonies from step 16 (see Subheading 3.3 or 3.4) by lightly touching the colony with a 20 μl pipette tip held vertically, removing a small amount of bacteria from the plate. Then swirl the tip in a PCR tube containing 50 μl of sterile water to release the bacteria from the tip (see Note 8). 2. Remove the pipette tip, close the tube, and heat solution at 95
C using a thermocycler for 5 min to lyse the cells. 3. Centrifuge for 5 min at 10,000  g. 4. Transfer 45 μl of supernatant (gDNA/water) without disturbing the pellet to a new microfuge tube. 5. Use 2 μl of the supernatant as a template in a 20 μl genomic PCR reaction (see Subheading 3.6).

GAANTRY Gene Stacking

3.6 Genomic PCR Validation of GAANTRY Assemblies

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1. Design primers that anneal and amplify amplicons that span the novel junctions created from each site-specific integration and excision event (Fig. 4) (see Note 9). 2. Use Taq polymerase, dNTPs, and amplification buffer, in combination with the ArPORT genomic DNA and the junctionspecific primers for polymerase chain reaction. 3. Run the genomic PCR reaction in the following program on a thermocycler: an initial denaturation step of 5 min at 95
C, followed by 35 cycles of 30 s at 95
C, 30 s at 56
C (this temperature will vary depending on the optimal annealing temperature of the primers used), and 2 min at 68
C (see Note 10), with a final extension at 68
C for 5 min. 4. Visualize the PCR amplification reactions using gel electrophoresis in a 1% agarose slab gel with known size standards spanning the range of sizes expected for the PCR amplicons. An example image of a genomic PCR validation of a 6-stack ArPORT1 strain is shown in Fig. 4.

3.7 Generation of Transgenic Plants

4

The GAANTRY system can be used to generate transgenic rice (Oryza sativa) plants or to genetically engineer other plant species. For Nipponbare rice transformation, seed-derived embryogenic calli can be transformed by co-cultivating with an Agrobacterium rhizogenes ArPORT1 strain carrying a stacked T-DNA using a previously described method [17]. The Thilmony lab has successfully used this procedure to generate more than 40 independent transgenic rice plants using GAANTRY ArPORT1 strains.

Notes 1. It is important to use freshly prepared plasmid DNA, especially when the cargo size is >10 kilobase pairs, since large Donor constructs recombine less efficiently. Transformation efficiency is also significantly reduced when old or poor-quality plasmid samples containing predominantly non-supercoiled plasmid DNA are used. 2. Multiple different methods for the generation of electrocompetent cells can successfully be used with GAANTRY assembly; however it is recommended that the room temperature method described by Tu and colleagues (see Subheading 3.2) be used for Donor plasmid constructs that are greater than 15 kilobases in size [16]. If electrocompetent cells are being premade for archiving at 80
C and later use with modestly sized donor vectors, then the method described by Collier and colleagues is preferred [14].

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Fig. 4 An example of the use of genomic PCR screening to validate a 6-stack GAANTRY assembly. A diagram of the 15.1 kilobase pair (kb) 6-stack T-DNA is shown on top. Each cargo sequence is displayed as a colored arrow. The T-DNA right border (RB) and left border (LB) locations are marked. The bacterial kanamycin selection marker gene (KanR) is shown on the right. Polymerase chain reaction (PCR) amplicons spanning each of the recombinase junctions are indicated by the numbered rectangles shown below the T-DNA diagram. A gel electrophoresis image of the seven PCR amplification products used to validate the 6-stack T-DNA assembly (a negative image of ethidium bromide-stained gel) is shown. The numbers above each lane correspond to the amplicons shown in the diagram. Molecular weight standards are shown on the left. The expected size of each amplicon (in base pairs) is shown above the amplicon band in the gel image

3. The best transformation efficiency occurs when cells in log phase growth (OD600 ¼ 0.4–0.6 which typically takes 3–4 h of growth at 30
C after starting from a saturated culture) are used. The transformation efficiency drops if the bacterial cells grow beyond an OD600 ¼ 0.6.

GAANTRY Gene Stacking

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4. For optimal results, the cells should be used immediately for electroporation. Tu and colleagues reported a 30% loss in transformation efficiency when the cells were stored at room temperature for 1 h, ~60% loss after 4 h, and ~80% loss after 24 h [16]. 5. Proper transformation occurs when no arcing within the electroporation cuvette is observed and a time constant of 4–5 ms is obtained. If the sample arcs, there is likely too much salt in the bacterial mixture or the plasmid DNA. To avoid this problem, use water to elute the plasmid DNA from the purification column (not the elution buffer provided in the plasmid isolation kit). If arcing persists, and the DNA was eluted in water, it is possible that the competent cells were not washed thoroughly enough; therefore, add an additional washing step (see Subheading 3.2, steps 7 and 8) to remove residual salts. Samples that arc within the electroporation cuvette typically will not produce colonies on the selection plate. 6. Plating the cells directly on medium with 5% w/v sucrose after transformation (skipping the initial selection on medium without sucrose) is not recommended. This will significantly decrease the number of colonies recovered and can lead to the recovery of clones that have not undergone complete GAANTRY-mediated integration and excision. 7. The GAANTRY stacking system relies on the iterative toggling between kanamycin and gentamicin resistance to insert additional sequences of interest; therefore, if a cargo sequence that expresses nptII in Agrobacterium is inserted into the T-DNA, it will block the ability to effectively use kanamycin selection for the insertion of additional cargo sequences. For example, inserting a CaMV35S promoter-nptII-nos terminator cargo sequence into ArPORT1 will confer kanamycin resistance, making the strain constitutively resistant to kanamycin. This will block the ability to use this strain for the insertion of additional cargo sequences carried in a P Donor plasmid. This phenomenon will be detected in the normal screening process by recovering colonies that are sucrose insensitive, but perpetually retain resistance to kanamycin. There are at least three ways to avoid this problem: (1) use promoter sequences on nptII cargo that do not express in Agrobacterium; (2) place a plant intron within the nptII coding sequence, blocking bacterial translation of a functional kanamycin resistance protein; or (3) stack the nptII-containing cargo sequence into the gene assembly last (when no more additional cargo needs to be added). Note, a similar problem will exist if a cargo sequence conferring bacterial resistance to gentamicin is added to the ArPORT1 T-DNA.

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8. Sample a colony using a 20 μl micropipette tip held vertically at a 90
angle relative to the petri plate. Touch the colony lightly to ensure that only a small number of cells are removed. Picking up too many bacteria can inhibit the PCR reaction or cause nonspecific amplification products to appear. 9. To allow the use of a single thermocycling program for screening with multiple PCR reactions, it is worthwhile to design primers with similar annealing temperatures and to make the amplicon sizes for each junction a unique size between 300 and 2000 base pairs. Choosing the size of the amplicon such that it is unique to each of the newly formed junctions enables the size of each amplicon to be diagnostic for a particular GAANTRY assembled sequence during agarose gel electrophoresis. In addition, it is also useful to design a pair of primers that can be used as a positive control for ArPORT1 strain genomic DNA. This primer pair can be used as a positive control PCR reaction from any ArPORT1 DNA sample. Since this simple genomic isolation procedure can fail by taking too many or too few bacterial cells (see Note 8), it is helpful to include a positive control PCR amplification reaction to validate that each genomic DNA sample is of sufficient quantity and quality for amplification. 10. The PCR extension time can vary depending on the type of polymerase that is used and the size of the expected amplicon. Typically, 1 min of extension at 68
C is used per kilobase of amplicon for Taq polymerase but follow the polymerase manufacturer’s instructions when designing the thermocycler amplification program. References 1. Gelvin SB (2003) Agrobacterium-mediated plant transformation: the biology behind the “gene-jockeying” tool. Microbiol Mol Biol Rev 67(1):16–37 2. Vain P (2007) Thirty years of plant transformation technology development. Plant Biotechnol J 5(2):221–229. https://doi.org/10. 1111/j.1467-7652.2006.00225.x 3. Dafny-Yelin M, Tzfira T (2007) Delivery of multiple transgenes to plant cells. Plant Physiol 145(4):1118–1128. https://doi.org/10. 1104/pp.107.106104 4. Ma L, Dong J, Jin Y, Chen M, Shen X, Wang T (2011) RMDAP: a versatile, ready-to-use toolbox for multigene genetic transformation. PLoS One 6(5):e19883. https://doi.org/10. 1371/journal.pone.0019883 5. Weber E, Engler C, Gruetzner R, Werner S, Marillonnet S (2011) A modular cloning

system for standardized assembly of multigene constructs. PLoS One 6(2):e16765. https:// doi.org/10.1371/journal.pone.0016765 6. Untergasser A, Bijl GJM, Liu W, Bisseling T, Schaart JG, Geurts R (2012) One-step Agrobacterium mediated transformation of eight genes essential for Rhizobium symbiotic signaling using the novel binary vector system pHUGE. PLoS One 7(10):e47885. https:// doi.org/10.1371/journal.pone.0047885 7. Zeevi V, Liang Z, Arieli U, Tzfira T (2012) Zinc finger nuclease and homing endonuclease-mediated assembly of multigene plant transformation vectors. Plant Physiol 158 (1):132–144. https://doi.org/10.1104/pp. 111.184374 8. Buntru M, G€artner S, Staib L, Kreuzaler F, Schlaich N (2013) Delivery of multiple transgenes to plant cells by an improved version of

GAANTRY Gene Stacking MultiRound Gateway technology. Transgenic Res 22(1):153–167. https://doi.org/10. 1007/s11248-012-9640-0 9. Binder A, Lambert J, Morbitzer R, Popp C, Ott T, Lahaye T, Parniske M (2014) A modular plasmid assembly kit for multigene expression, gene silencing and silencing rescue in plants. PLoS One 9(2):e88218. https://doi.org/10. 1371/journal.pone.0088218 10. Shih PM, Vuu K, Mansoori N, Ayad L, Louie KB, Bowen BP, Northen TR, Loque´ D (2016) A robust gene-stacking method utilizing yeast assembly for plant synthetic biology. Nat Commun 7:13215. https://doi.org/10.1038/ ncomms13215 11. Cermak T, Curtin SJ, Gil-Humanes J, ˇ egan R, Kono TJY, Konecˇna´ E, Belanto JJ, C Starker CG, Mathre JW, Greenstein RL, Voytas DF (2017) A multi-purpose toolkit to enable advanced genome engineering in plants. Plant Cell. https://doi.org/10.1105/tpc.16.00922 12. Zhang H-Y, Wang X-H, Dong L, Wang Z-P, Liu B, Lv J, Xing H-L, Han C-Y, Wang X-C, Chen Q-J (2017) MISSA 2.0: an updated synthetic biology toolbox for assembly of orthogonal CRISPR/Cas systems. Sci Rep 7:41993. https://doi.org/10.1038/srep41993 13. Zhu Q, Yu S, Zeng D, Liu H, Wang H, Yang Z, Xie X, Shen R, Tan J, Li H, Zhao X, Zhang Q, Chen Y, Guo J, Chen L, Liu Y-G (2017) Development of “purple endosperm rice” by

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engineering anthocyanin biosynthesis in the endosperm with a high-efficiency transgene stacking system. Mol Plant 10(7):918–929. https://doi.org/10.1016/j.molp.2017.05. 008 14. Collier R, Thomson JG, Thilmony R (2018) A versatile and robust Agrobacterium-based gene stacking system generates high-quality transgenic Arabidopsis plants. Plant J 95 (4):573–583. https://doi.org/10.1111/tpj. 13992 15. Green MR (2012) In: Green MR, Sambrook J (eds) Molecular cloning : a laboratory manual. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NYVolume accessed from https://nla.gov.au/nla.cat-vn6039452 16. Tu Q, Yin J, Fu J, Herrmann J, Li Y, Yin Y, Stewart AF, Muller R, Zhang Y (2016) Room temperature electrocompetent bacterial cells improve DNA transformation and recombineering efficiency. Sci Rep 6:24648. https:// doi.org/10.1038/srep24648 17. Sallaud C, Meynard D, van Boxtel J, Gay C, Bes M, Brizard JP, Larmande P, Ortega D, Raynal M, Portefaix M, Ouwerkerk PB, Rueb S, Delseny M, Guiderdoni E (2003) Highly efficient production and characterization of T-DNA plants for rice (Oryza sativa L.) functional genomics. Theor Appl Genet 106(8):1396–1408. https://doi.org/10. 1007/s00122-002-1184-x

Chapter 2 TransGene Stacking II Vector System for Plant Metabolic Engineering and Synthetic Biology Qinlong Zhu and Yao-Guang Liu Abstract Efficient stacking of multiple genes is a critical element in metabolic engineering of complex pathways, synthetic biology, and genetic improvement of complex agronomic traits in plants. Here we present a highefficiency multigene assembly and transformation vector system, TransGene Stacking II (TGS II), for these purposes. The operation process is described in detail, and the successful operation mainly depends on effective reagents, special Escherichia coli strains, and basic molecular biological means without other specific equipments. Key words Metabolic engineering, Synthetic biology, Multigene stacking, Gene assembly, Cre/loxP

1

Introduction For engineering complex metabolic pathways and genetic improvement of complex agronomic traits in plants, an effective multigene stacking system is critical to assemble and transfer multiple genes into plants [1–3]. Compared with other transgene-stacking strategies, such as co-transformation of multiple plasmids, retransformation, and crossing between transgenic plants, it is more advantageous to utilize transgene-stacking vectors that enable assembly of multiple genes into single constructs for plant transformation [4, 5]. However, the construction of multigene vectors has long been difficult due to the limited number of available restriction enzyme sites and the low ligation efficiency for large plasmids. Currently, several different strategies have been used to develop transgene-stacking vector systems for assembling limited numbers of target genes, for example, using rare-cutter endonuclease sites and homing endonuclease sites [6], MultiSite Gateway [7], homologous recombination in yeast [8], or a recent method using recombination in Agrobacterium tumefaciens [9].

Anindya Bandyopadhyay and Roger Thilmony (eds.), Rice Genome Engineering and Gene Editing: Methods and Protocols, Methods in Molecular Biology, vol. 2238, https://doi.org/10.1007/978-1-0716-1068-8_2, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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Our previous study has developed a transgene-stacking system, using Cre/loxP recombination of donor-target gene plasmids into an acceptor binary vector, and then releasing donor plasmid backbone by homing endonuclease digestion, followed by final ligation with a linker [10]. This early version can assemble multigene into an acceptor vector that uses the transformation-competent artificial chromosome (TAC) as vector backbone, which is capable to carry and transfer large-size DNA fragments (>100 kb) into plants [11, 12]. Nevertheless, this early system still remains challenge for assembling large number of genes, due to inefficient homing endonuclease digestion and linker ligation for large plasmids in vitro. Here, we describe a flexible and high-efficiency transgene stacking vector system TGS II for assembling and transferring multiple genes in plants [13]. The basic TGS II system consists of three parts (Fig. 1a): a set of binary acceptor vectors (see Note 1), two donor vectors for subcloning target genes, and an optionally used selectable marker/marker excision donor vectors. The binary acceptors have a set of key components [loxP/I-Sce I/loxP1R: a wild-type loxP site, a homing endonuclease I-Sce I, and a mutant loxP site (loxP1R)] for multi-round target gene assembly cycling. By Cre-mediated loxP recombination in E. coli host cells, the donor vector plasmids containing target genes are integrated alternatively into the acceptor, followed by removing the donor vector backbone via Cre-mediated irreversible recombination between a paired compatible mutant loxP sites (loxP1L and loxP1R or loxP2L and loxP2R). As a final step, the selectable marker cassette/marker excision cassette is incorporated into the acceptor that carries the assembled target genes using Gateway BP reaction. The marker/ marker excision cassette in transgenic plants is deleted by Cre/loxP recombination controlled by a tissue-specific or conditional promoter. Because the TGS II system is able to automatically remove the donor vector backbone in vivo from the intermediate recombinant plasmids without restriction and ligation steps, it is more simple and efficient than our previous transgene-stacking vector system [13, 14]. Using the TGS II system, we have developed a serial of new rice germplasms bioflorified with phytonutrients, such as the “Purple Endosperm Rice” (also called “Zi Jingmi” in Chinese) [13, 15] and the “Astaxanthin Rice” or “aSTARice” (also called “Chi Jingmi” in Chinese) [16, 17]. The binary construct for rebuilding the anthocyanin biosynthetic pathway in endosperm had eight anthocyanin pathway genes and two genes (a selectable marker and a marker excision cassette) for marker excision. TGS II also can be used as a vector platform to develop different complex vectors such as our plant CRISPR/Cas9 vectors [18]. Importantly, this multigene assembly system also can be adapted for genetic engineering in other non-plant organisms, simply by inserting the key components loxP/I-Sce I/loxP1R into other suitable vector plasmids to create

TransGene Stacking II Vector System for Plant Metabolic Engineering and. . .

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Fig. 1 Overview of the TransGene Stacking II system. (a) The composition of TGS II system. The representative binary acceptor vector pYLTAC380GW contains the key component sequence (loxP/I-Sce I/loxP1R) for accepting multiple genes from target gene donors and the Gateway recipient region containing the SacB gene for recombining the marker-free competent cassette derived from the marker/marker excision donor vectors. SacB is a lethal gene in E. coli in the presence of 5% sucrose and serves as a negative selection

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new types of acceptor vectors, which can be used in combination with the same donor vectors. Due to the advantages of easy manipulation and high efficiency, we expect that the TGS II system will have more potential applications in synthetic biology, multigene metabolic engineering of complex pathways, and genetic improvement of complex agronomic traits.

2

Materials

2.1 General Molecular Biology Reagents

1. DNA oligonucleotides (purified by desalt) for cloning of genes or colony PCR screening (Sangon Biotech, Guangzhou, CHN). 2. PCR reagents: Taq DNA polymerase and PCR mix buffer (GenStar, Beijing, CHN) for clone analysis. High-fidelity polymerases KOD FX (TOYOBO, Osaka, JAP) or Phanta™ SuperFidelity DNA Polymerase (Vazyme, Nanjing, CHN) for gene subcloning. 3. Restriction enzymes: homing endonucleases (I-SceI and PI-SceI) and other chosen enzymes for restriction analysis (New England Biolabs, MA, USA). 4. T4 DNA ligase (400 U/μl, New England Biolabs, MA, USA). 5. Sterilized ultrapure water ddH2O (RNase-/DNase-free). 6. TIANGEN Gel Extraction Kit, TIANGEN PCR Purification Kit, and TIANGEN Miniprep Plasmid Kit (TIANGEN Biotech, Beijing, CHN). QIAprep Spin Miniprep Kit (Qiagen, CA, USA). 7. GelStain, 6X DNA gel loading dye, and 1- or 15-kb Plus DNA Ladder (TransGen Biotech, Beijing, CHN). 8. General gel electrophoresis reagents and apparatus. 9. Millipore dialysis membrane (0.025 μm VSWP, VSWPO4700, Merck Millipore Ltd., Cork, IRL).

Cat.


Fig. 1 (continued) marker. Pv4 is a pollen-specific promoter for driving Cre expression. The other binary acceptor vectors of TGS II are shown in the previous report [13]. (b) Schematics of multigene assembly. One or more target genes (A–F) are subcloned into the donor vectors. In each gene assembly cycle (a round of recombination), there are two reactions mediated by Cre: the first reaction occurs between the wild-type loxP sites to integrate a donor vector with target gene(s) into an acceptor (i) and the second one between the mutant loxP sites (loxP1L and loxP1R or loxP2L and loxP2R) is irreversible, which removes the donor vector backbone (ii). These recombination processes are automatically completed in the transformed E. coli strain NS3529 cells that express Cre. In pollen of transgenic plants, Cre/loxP-recombination deletes the marker gene and Cre. (c) An example of multigene binary construct and verification of the assembled eight genes for anthocyanin biosynthesis in rice endosperm, by Not I (N)-digestion. This figure is modified from the previous report [13]

TransGene Stacking II Vector System for Plant Metabolic Engineering and. . .

23

10. Gene Pulser Xcell™ Electroporation Systems (Bio-Rad, USA). 11. SOC liquid, LB liquid, and LB agar. 12. Ampicillin (Amp), chloramphenicol (Chl), and kanamycin (Kan) antibiotics. 13. Gateway BP Clonase II enzyme mix (Thermo Fisher Scientific, CA, USA). 14. Tris-EDTA (TE) buffer, pH 8.0. 2.2

Microbial Strains

1. Electro-competent cells of E. coli strains NS3529 (expressing Cre) and DH10B. 2. Electro-competent cells of A. tumefaciens strain (EHA105).

2.3

Vector Plasmids

1. Acceptor vectors: pYLTAC380GW (with a sucrose-induced lethal SacB gene as a negative selectable marker), pYLTAC380 (without a selectable marker gene) and pYLTAC380H/N/B (with HPT/NPTII /Bar selectable marker genes) based on TAC backbone, pYL0380 (without marker genes), and pYL1305H (with a HPT selectable marker gene) based on pCAMBIA backbone, in which GenBank numbers are KY420084, KY420080, KY420081, KY420082, KY420083, KY420078, and KY420079, respectively. 2. Donor vectors: pYL322d1 (GenBank No. KY420076) and pYL322d2 (GenBank No. KY420077) are based on pBR322 backbone and their MCS (multiple cloning sites) have 18 single restriction sites for cloning several target genes or large fragments (up to ~20 kb). 3. Marker/marker excision donor vectors: pYLMF-H (GenBank No. KY420085), pYLMF-N (GenBank No. KY420086), and pYLMF-B (GenBank No. KY420087) have the HPT, NPT II, and Bar selectable marker genes, respectively, and the Cre gene driven by a pollen-specific promoter (Pv4).

3

Methods

3.1 Propagation of Acceptor Vectors (See Note 1)

1. Electroporation of ca. 2 ng pYLTAC380GW plasmid (or other acceptors) into electro-competent cell DH10B and pre-culture in 1 ml SOC liquid medium at 37
C for 1 h. 2. Plate 50 μl transformed cells on one LB agar plate supplemented with Kan (25 μg/ml) and the same volume (50 μl) cells on another LB agar plate supplemented with Kan (25 μg/ml) and 5% sucrose (for pYLTAC380GW with SacB). Culture the plates at 37
C overnight. If there are no or only very small colonies appearing on the plate with sucrose, the SacB gene is proved to be functionally active.

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Qinlong Zhu and Yao-Guang Liu

3. Inoculate several colonies into 3 ml each of LB medium containing Kan (25 μg/ml), and culture with 250 rpm at 37
C for overnight. For TAC-based acceptors with the P1 lytic replicon (see Fig. 1a), the LB medium contains 0.5 mM IPTG (see Note 2). 4. Extract and purify the plasmids using QIAprep Spin Miniprep Kit or TIANGEN Miniprep Plasmid Kit according to the manufacturer’s instructions, and then elute the plasmids with 0.5 TE (see Note 3). 5. Quantify the concentration of the purified plasmids. 6. Verify the purified acceptor plasmids with Not I-digestion: mix 1.5 μl 10 CutSmart buffer, ca. 400 ng plasmid, 5 U Not I, adding ddH2O to total 15 μl, and incubate at 37
C for 1 h. 7. Perform gel electrophoresis of the digested plasmid on an agarose gel (1% w/v) along with an appropriate DNA ladder (1–15 kb); digested pYLTAC380GW has three bands of 1.29, 1.53, and 15.2 kb, respectively. The different types of acceptor vectors have different Not I site maps (see Note 4). 3.2 Propagation of Donor Vectors

1. Transfer ca. 1 ng of pYL322d1 and pYL322d2 into DH10B electro-competent cells (or other chemically competent cells, e.g., DH5α), respectively. Plate 20 μl each of the cells on a LB agar plate containing Chl (15 μg/ml) for pYL322d1 or Amp (70 μg/ml) for pYL322d2, and culture at 37
C for overnight. 2. Culture colonies and prepare the plasmids as described in Subheading 3.1 steps 3–5, but use LB medium containing Chl (15 μg/ml) for pYL322d1 or Amp (70 μg/ml) for pYL322d2. 3. Mix 1.5 μl 10 CutSmart buffer, ca. 200 ng plasmid, 2–3 U Hind III, adding ddH2O to total 15 μl, and incubate at 37
C for 0.5 h. 4. Verify the digested plasmids that produce a single band of ~3.0 kb on a 1% agarose gel.

3.3 Propagation of Marker/Marker Excision Donor Vectors (See Note 5)

1. Transfer ca. 1 ng pYLMF-H/B/N into DH10B (or other strain). 2. Prepare plasmids as described in Subheading 3.1, steps 3–5, but use LB medium plus Amp (70 μg/ml). 3. Verify plasmids using Asc I/Hind III double digestion by mixing 1.5 μl 10 CutSmart buffer, ca. 300 μg plasmid, 2–3 U Hind III, 2–3 U Asc I, adding ddH2O to total 15 μl, and incubate at 37
C for 30 min. 4. Perform gel electrophoresis of the digested plasmids and check the two bands in size of ~4.9 to ~4.3 kb for different marker/ marker excision cassettes and ~2.8 kb for the backbone.

TransGene Stacking II Vector System for Plant Metabolic Engineering and. . .

3.4 Subcloning Target Genes into the Donor Vectors

25

The target gene expression cassettes, containing promoters, CDS (coding sequence), and terminators, can be subcloned separately or as a whole into MCS of the donor vectors, using the conventional restriction-ligation method or other ways such as the Omega-PCR [19] and the modified Gibson cloning methods [20, 21] (see Note 6). Target gene(s) for odd-numbered assembly cycles are subcloned into pYL322d1, and those for even-numbered are subcloned into pYL322d2 (Fig. 1b). The LacZ gene in the donor vectors is not used as a marker for subcloning target genes (see Note 7). More than one (e.g., two) genes also can be subcloned into the same donor vector by multistep of conventional restriction-ligation or one round of Gibson cloning as described [21]. The orientation of a target gene cassette (promoter-CDS-terminator) assembled into the T-DNA of an acceptor vector is the same with its orientation in the donor vectors, and the order of target genes in the T-DNA region is from the RB side to the LB side (Fig. 1b and see Note 8). Below is an example of using the restriction-ligation for subcloning: 1. PCR-amplify a gene or a DNA fragment using high-fidelity polymerases such as KOD FX or Phanta™ Super-Fidelity DNA Polymerase using specific primers containing selected cloning restriction sites in the MCS of the donor vector. 2. Purify the PCR products using a gel extraction kit, elute DNA in 25 μl ddH2O, and determine the DNA concentration. 3. Digest donor plasmids DNA (0.5–1 μg) and purified PCR products (0.5–1 μg) with the selected restriction enzymes. Run the fragments on 0.8% agarose gel and purify them with a DNA extraction kit. 4. Use the NEBioCalculator tool (http://nebiocalculator.neb. com/#!/ligation) to calculate molar ratios, and ligate the digested donor plasmid (ca. 50 ng) and target gene with a molar ratio of 1:3 in 10 μl with ca. 200 U T4 DNA ligase at 16
C for 2–3 h. 5. Transfer the ligation product into DH10B as described in Subheading 3.2, steps 1–3. 6. Pick several resistant colonies for colony PCR screening using gene-specific primers, with PCR program: 94
C for 5 min, 33 cycles of 94
C for 30 s, 56
C for 30 s, 72
C for 60 s/kb, 72
C for 5 min. 7. Prepare the plasmid from several PCR-positive colonies, and digest each plasmid sample (ca. 300 ng) with 5 U Not I to release individual gene from the donor vector backbone (~3.0 kb). Analyze the digested DNA on 0.8% agarose gel. 8. Sequence the two insert ends of the positive clones using primers (SP6m, 50 -GGTGACACTATAGCCAAGC-30 , and T7, 50 -AATACGACTCACTATAGGG-30 ) that flank the MCS of the donor vectors.

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Qinlong Zhu and Yao-Guang Liu

3.5 The First Round of Gene Assembly (Round I)

For one round of assembly in vivo in E. coli strain NS3529, one or more genes can be delivered into the binary accept vector. After the Round I (and odd-numbered cycles) of gene assembly, a digestion with homing endonuclease I-Sce I is performed to eliminate background plasmids and recover the target recombination plasmid (see Note 9). 1. Mix ca. 10–15 ng donor plasmid pYL322d1-A (A represents a target gene or a gene set) and ca. 30–50 ng the primary acceptor plasmid (e.g., pYLTAC380GW) (in molar ratio of about 1:1 to 2:1) in 1.0–1.5 μl and electroporate the plasmids into competent cells of E. coli strain NS3529 (see Note 10). 2. Pre-culture the transformed competent cells in 1 ml SOC liquid medium at 37
C for 1–1.5 h with shaking (150–200 rpm), and then plate 200 μl of the cells onto a LB agar plate supplemented with Kan (25 μg/ml) and Chl (15 μg/ ml) at 37
C for ca. 16–18 h. 3. Directly pool several hundred colonies (by washing the colonies with ddH2O from the plate), and perform minipreparation of the plasmids (if there are only few colonies, see Note 11), using conventional alkaline lysis method (with RNase in Solution I) or a kit (the washing 70% ethanol should be completely removed; see Note 3). 4. Digest the plasmids (including four types of plasmids) with a homing endonuclease I-Sce I (see Note 9): add 1 μl 10 CutSmart buffer, 0.5 μl (5 U/μl) I-Sce I, ca. 70–100 ng plasmids, and ddH2O to total 10 μl; incubate the reaction at 37
C for 1–2 h. 5. Dialyze the digested plasmids against 1/3 TE using the dialysis membrane at 4
C for 0.5–1 h; then electroporate 1 μl the dialyzed product into DH10B competent cells (or other stains without the Cre gene). Spread 200 μl the pre-cultured transformed cells on LB agar plates containing 25 μg/ml Kan supplemented with 0.5 mM IPTG and 40 μl X-gal (20 mg/ml) (see Note 7), and incubate at 37
C for 16–20 h. Blue colonies are those with the coexistence of the donor vector or with intermediate recombinant plasmid (see Note 7). 6. Pick up several white colonies and suspend each into 10 μl ddH2O (in tubes), and take 1 μl diluted colony cells directly for PCR screening (the remaining cells are stored for later cell culture for plasmid preparation). Two primers are used for this screening: one is located on the acceptor vector (e.g., 380F, 50 -GCAAACAGCTATTATGGGTGTC-30 located in the PI-Psp I site region (see Fig. 1a) and another is located on the target gene, Fig. 2). Only clones with correctly integrated target gene are PCR-positive.

TransGene Stacking II Vector System for Plant Metabolic Engineering and. . .

LB

27

PI-Psp I Target gene

RB

Vector-specific primer 380F Gene-specific primer

Fig. 2 Location of the primers used for PCR analysis of inserted target gene

7. Inoculate 5 μl each PCR-positive colony cells into 2.0–3.0 ml LB with 25 μg/ml Kan and 0.5 mM IPTG (for induction of the P1 lytic replicon for high yield of the plasmid), and culture at 37
C overnight. 8. Prepare the plasmid as described in Subheading 3.1, steps 3–5, and digest the plasmid (ca. 500 ng) with 5 U Not I as described in Subheading 3.4, step 7. Correct recombinant plasmids show one band more (if there is no Not I site within the target gene) than the control (starting acceptor vector) (Fig. 1c). 9. Sequence the plasmid (Acceptor-A) using the 380F primer (or the target gene-specific reverse primer) to identify the integrity of the recombination sites and gene A. For odd-numbered assembly cycles, the resultant correct recombination sites are loxP/PI-SceI/loxP2R (Fig. 1b). 3.6 The Second Round of Gene Assembly (Round II)

One or more genes (e.g., two) also can be subcloned into the donor vector pYL322d2. For the second round of assembly in NS3529, one or more genes can deliver into the recombinant binary acceptor vector from the round I assembly. After the round II (evennumbered cycles) of gene assembly, a digestion with a homing endonuclease PI-Sce I is performed (see Note 9). 1. Mix ca. 10–15 ng donor plasmid pYL322d2-CB (in this example, two genes B and C are cloned into the same donor vector) and ca. 50 ng Acceptor-A plasmid (in a molar ratio of 1:1 to 2:1) in 1–1.5 μl, and electroporate the plasmids into NS3529 cells (see Note 10). Spread and culture the transformed cells as described in Subheading 3.5, step 2, but use LB agar plate plus Kan (25 μg/ml) and Amp (70 μg/ml). 2. Collect several hundred colonies for plasmid mini-preparation (if there are few colonies, see Note 11) as described in Subheading 3.5, step 3. Digest the mixed plasmids with a homing endonuclease PI-Sce I to cut background plasmids (the target recombinant plasmid has no the PI-Sce I site; see Note 9): add 1 μl 10 NEBuffer for PI-Sce I, 0.1 μl 100 BSA, 0.5–0.8 μl (5 U/μl) PI-Sce I, 40–60 ng (no more than 100 ng) the plasmids, and ddH2O to total 10 μl. Incubate the reaction at 37
C for 1–2 h.

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Qinlong Zhu and Yao-Guang Liu

3. After dialysis, electroporate 1 μl the digested product into DH10B cells as described in Subheading 3.5, step 5. 4. Select several white colonies for colony PCR screening using the acceptor vector primer (380F) and a primer of the last target gene (gene C), as described in Subheading 3.5, step 6. Digest PCR-positive plasmids using Not I as described in Subheading 3.5, steps 7 and 8. Correct recombinant plasmid (Acceptor-C/B/A) shows one band more than the control (Acceptor-A) (Fig. 1b, c). 5. Sequence the plasmid (Acceptor-C/B/A) using 380F (or the gene-C primer) to identify the integrity of the recombination sites. For even-numbered assembly cycles, the resultant correct recombination sites are loxP/I-Sce I/loxP1R (Fig. 1b). 3.7 More Round of Assembly Cycles

The recombinant plasmid obtained from the latest round recombination is used as new acceptor for next round recombination. According to the order of odd-even numbers of target genes in the donor vectors, the odd-numbered ones are integrated into the acceptor through operation showing in round I, while the evennumbered ones are done as showing in round II. Using this strategy, multiple genes can be sequentially delivered into a binary acceptor vector. 1. For round III (and other odd-numbered) gene assembly (Fig. 1b), co-transfer Acceptor-C/B/A (the latest round recombinant acceptor plasmid) and new pYL322d1-E/D (containing target genes E and D as an example) into NS3529. Then use I-Sce I to digest the plasmids, and transform DH10B to produce the new recombination plasmid AcceptorE/D/C/B/A, as described in Subheading 3.5. 2. For round IV (and other even-numbered) gene assembly (Fig. 1b), transfer the mixture of Acceptor-E/D/C/B/A (the latest round recombinant acceptor plasmid) and pYL322d2-F (containing target gene F as an example) into NS3529. Then use PI-Sce I to digest the plasmids, and transform DH10B to produce the new recombination plasmid Acceptor-F/E/D/C/B/A, as described in Subheading 3.6.

3.8 Marker/Marker Excision Cassette Assembly

To prepare a marker-free competent multigene construct, the acceptor pYLTAC380GW must be used as the initial acceptor vector for the gene assembly. After completing the assembly of all target genes, the selectable marker/marker excision cassette is recombined into the pYLTAC380GW-based multigene acceptor vector (e.g., pYLTAC380GWlllC/B/A) by Gateway BP reaction to generate the final binary construct (Fig. 1b).

TransGene Stacking II Vector System for Plant Metabolic Engineering and. . .

29

1. Mix the completed target gene plasmid pYLTAC380GWlllC/ B/A (150 ng) and a selectable marker/marker excision donor plasmid (100 ng), and add ddH2O to total 8 μl. 2. Thaw 5x Gateway BP Clonase II enzyme mix on ice and vortex briefly, add 2 μl the enzyme mix to the reaction and vortex briefly, and then incubate at 25
C for 5–8 h (see Note 12). 3. Add 1 μl of proteinase K solution (2 μg/μl) at 37
C for 10 min to stop the reaction. After dialyzing against on 1/3 TE, electroporate 1 μl the product into DH10B, and spread 200 μl the transformed cells on an LB agar plate containing 25 μg/ml Kan supplemented with 5% sucrose. 4. Pick up several colonies for PCR screening using one or two of the primer pairs. The first pair primers are for detecting the linking region with the marker genes using Fm-1/Rm (Fig. 3a; Rm ¼ Rh, Rn, or Rb) (Fm-1 locating on pYLTAC38 0GWlllC/B/A, 50 -AATTAATTCCTAGGCCACCATGTTG30 ; Rh for HPT, 5-GTCTGGACCGATGGCTGTGTAG-3; Rn for NPTII , 5-CCGATTCGCAGCGCATCGC-3; and Rb for Bar, 50 -GGCTTCAAGCACGGGAACTG-3). These PCR fragments are about 0.55 kb in length. The second pair primers are for detecting linking region with the Pv4 promoter: FPv4/ Rg-o (FPv4, 50 -GGGCCCATGTTCTTGAGGTATCTC-30 , and Rg-o for last odd-numbered assembly, 5-CCGCATG CATCGATCTCCT-3, or FPv4/Rg-e (Rg-e for last evennumbered assembly, 5-GGCCATGCCCTCCATCCT-3). These PCR products are about 0.5 kb in length (Fig. 3a). 5. Prepare the PCR-positive plasmids (pYLTAC380MFlllC/B/ A) and confirm them by Not I digestion as described in Subheading 3.1, steps 4–7, which show two more bands (2.1-kb HPT/1.9-kb NPTII/1.6-kb Bar marker gene and 3.2-kb Cre marker deletion gene) than the control plasmid (pYLTAC380GWlllC/B/A) (Fig. 1c). 6. Sequence the plasmid clones (pYLTAC380MFlllC/B/A) using Fm-1 to identify the inserted marker gene and Rg-o (for odd-numbered assembly) or Rg-e (for even-numbered assembly) to identify the inserted Cre marker deletion gene cassette. 3.9 Analysis of Structural Stability of Multigene Constructs in A. tumefaciens

To test structural stability of the multigene plasmid in an A. tumefaciens, the plasmid isolated from the strain EHA105 is transferred back into E. coli DH10B; then restriction analysis is performed (see Note 13). 1. Electroporate ca. 10 ng the multigene plasmid (e.g., pYLTAC380MFlllC/B/A) into EHA105 electro-competent cell (or another appropriate strain), and pre-culture in 1 ml YM liquid medium at 28
C for 2 h.

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Qinlong Zhu and Yao-Guang Liu

a

~5.4 kb Fm-1

Round n-1 (odd number)

recombination

RB

LB T35S marker P35s Tnos Cre

D

Pv4

C

A

B

attL2

attL1

Rm

Rg-o

Fpv4

~ 0.55 kb

~ 0.50 kb

Excision

Cre expression driven by the pollen-specific promoter Pv4 RB

LB D

C

A

B

attL1

~ 0.3 kb

Fm-1

Rg-o 5.4 kb

b

Fm-1

Round n (even number)

recombination

RB

LB T35S marker P35s Tnos Cre

Pv4

D

B

C

A

attL2

attL1

Rm

Rg-e

Fpv4 ~ 0.50 kb

~ 0.55 kb

Excision

Cre expression driven by the pollen-specific promoter Pv4 RB

LB D

C

B

A

attL1

~ 0.3 kb

Fm-1

c

bp

Rg-e

PER-Z#3

PER-Z#14

750 500 250 100

T1 plants

PER-Z#3

PER-Z#14

750 500

T2 plants

250 100

d

attL1 (part)

loxP

I-Sce I

1R

Fig. 3 Schematic diagram showing primers and sequences for PCR analysis of marker-free plants. (a) The 0.3kb PCR fragment (using Fm-1/Rg-o) after the marker excision from a T-DNA from odd-number rounds of gene

TransGene Stacking II Vector System for Plant Metabolic Engineering and. . .

31

2. Spread 100 μl the transformed cells on YM agar plates containing 25 μg/ml Kan and 35 μg/ml Chl, and incubate at 28
C for 2 days. 3. Pick up several colonies to culture in 2 ml YM liquid medium (plus 25 μg/ml Kan and 35 μg/ml Chl) at 28
C for 36 h, and then isolate plasmids as described in Subheading 3.1, step 4. 4. Re-electroporate 1 μl (ca. 2 ng) the multigene plasmid from EHA105 into E. coli DH10B, and isolate the plasmid. 5. Verify the plasmid structure by Not I digestion as described in Subheading 3.4, step 7, and compare the digested plasmid pattern from EHA105 to that of the original one (Fig. 1c). 3.10 Fast Test of Marker Deletion in E. coli NS3529

For rapid testing whether the marker/marker excision cassette can be deleted by Cre, the marker-free competent multigene vector (e.g., pYLTAC380MFlllC/B/A) can be transferred into E. coli strain NS3529 that expresses Cre. PCR analysis of marker-excised colonies shows a 0.3-kb band, which indicates that the marker deletion occurs between the loxP sites by Cre-mediated recombination (Fig. 3). 1. Electroporate ca. 2 ng the multigene plasmid (e.g., pYLTAC380MFlllC/B/A) into E. coli strain NS3529 as described in Subheading 3.5, step 1; grow colonies on LB agar plate with 25 μg/ml Kan at 37
C for overnight. 2. Pick up several colonies for PCR analysis using one pair of primers (Fm-1/Rg-o or Fm-1/Rg-e, Fig. 3) as described in Subheading 3.8, step 4. 3. Perform gel electrophoresis of the PCR products and verify the 0.3-kb band (Fig. 3). 4. Sequence the 0.3-kb PCR fragment with Rg-o or Rg-e to confirm the deletion.

3.11 Analysis of Marker Deletion in Transgenic Plants (See Note 14)

To select T1 or T2 plants (rice) with marker deletion, perform PCR analysis with the three primers (Fm-1, Rm (Rh, Rn, or Rb), and Rg-o (or Rg-e)) (Fig. 3a, b). In T1 plants, detection of two bands (0.55 and 0.3 kb) indicates the deletion of the marker gene cassette in a hemizygous state. In T2 plants, detection of only the 0.3-kb


Fig. 3 (continued) assembly. (b) The 0.3-kb fragment (using Fm-1/Rg-e) after the marker excision from a T-DNA from even-number rounds of gene assembly. (c) An example of PCR detection of marker-free transgenic rice plants (from lines PER-Z#3, #14) using the three primers. In T1 plants, two fragments (0.55 and 0.3 kb) were amplified, which are heterozygotes for the marker excision. In T2 plants, detection of the 0.3kb band only (arrowed) shows homozygotes for the fragment deletion. (d) Sequencing of 0.3-kb PCR fragment shows that the marker/Cre gene cassette gene is precisely deleted as expected. Parts of this figure are modified from the previous report [13]

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Qinlong Zhu and Yao-Guang Liu

band indicates the deletion of the marker gene cassette in a homozygous state (Fig. 3d). The 5.4-kb fragment is too large to be amplified in the PCR condition (with 30 s for extension).

4

Notes 1. Acceptor vectors include a serial of constructs based on the TAC backbone (pYLTAC380, pYLTAC380H/N/B, and pYLTAC380GW) or pCAMBIA backbone (pYL0380 and pYL1300H). Selection of an appropriate binary acceptor vector for multigene stacking depends on whether or not getting marker-free plants and the size of finally assembled genes. For marker-free transgene stacking, the pYLTAC380GW acceptor must be used. For assembly of genes with total sizes of less than 20 kb, a pCAMBIA-based or a TAC-based acceptor vectors can be used. For assembly of genes with total sizes of larger than 20 kb, a TAC-based vector should be used. 2. The TAC-based acceptors have a P1 plasmid replicon and a P1 lytic replicon. The P1 plasmid replicon can stably carry large DNA up to ~100 kb, but it maintains the plasmid in single copy thus low plasmid yield. To increase plasmid yield, IPTG can be added into the culture to final 0.5 mM to induce the P1 lytic replicon for moderate copy number. The CAMBIA-based acceptors use the pBR322 replicon to produce moderate copy plasmid. 3. Before dissolving the plasmids using ddH2O or TE, DNA mini-preparation kit columns should be heated on the metal hot block at 65
C for 3 min to completely remove the washing 70% ethanol; any residual ethanol may inhibit the restriction enzyme activity. 4. The pVS1 replicon of the acceptor vectors contains three Not I sites. For pYLTAC380 and pYLTAC380GW empty acceptor vectors, the Not I-digested backbone shows two small bands in size of 1.29 and 1.53 kb and one large band in size of ~13 and ~15 kb, respectively. For pYLTAC380H/N/B and pMF-H/ N/B, other two Not I sites are located on the both sides of the HPT (2.1 kb)/NPTII (1.9 kb)/Bar (1.6 kb) expression cassette, respectively. For empty CAMBIA-based acceptors, the Not I-digested backbone has the same two small bands as TAC-based acceptor vectors, but the large band is smaller in sizes of ~4.2 to ~6.6 kb. The detailed sequence and maps of those vectors are shown in the previous report [13]. 5. PV4 is a rice pollen-specific promoter from Villin4 (Os04g0604000) for driving Cre expression in pollen of rice and also may be in other monocot plants. When these vectors

TransGene Stacking II Vector System for Plant Metabolic Engineering and. . .

33

are to be used in other dicot plants, it is recommended to replace this promoter using another suitable pollen promoter to drive Cre. Because there are no restriction enzyme sites for cutting out PV4, the restriction-ligation-independent methods of the Omega-PCR [19] or modified Gibson method [21] can be used to perform this modification. The sequences of site 1 (5-GAAGGAGAAAAACTAGAAATTTACGACAT-3) and site 2 (5-GAGCCACCTCTATCCTACT GCAAC-3) are designed for Omega-PCR or Gibson cloning to replace PV4 with another appropriate promoter. 6. Target genes or DNA fragments can be subcloned into any sites of the MCS of the donor vectors. If they are inserted in the sites between the two Not I sites, they can be easily checked in the acceptor vector by Not I digestion. 7. In procedures 3.5 and 3.6, LacZ in the donor vectors is used to indicate blue colonies with co-transferred acceptor and donor plasmids, or those colonies carrying immediate acceptor-donor recombinant plasmid, of which the donor vector backbone is not removed. Therefore, in subcloning of target genes into the donor vectors, IPTG and X-gal are not necessary to be added in the LB agar plates. 8. In general the relative orientations of the target genes or DNA fragments in the T-DNA may not be an important factor affecting the gene expression, but in some cases the users can arrange the genes in certain order and relative orientation in the T-DNA region. 9. The plasmids isolated from NS3529 include (1) the un-recombinant donor plasmid, (2) the un-recombinant acceptor plasmid, (3) immediate recombinant plasmid (e.g., donor vector backbone is unremoved), and (4) the target plasmid. The background plasmids (1)–(3) contain one or two of the homing endonuclease site (I-Sce I for odd-numbered cycles and PI-Sce I for even-numbered cycles), but the target plasmid lacks the corresponding homing endonuclease site. Therefore, digestion with homing endonuclease I-Sce I (for odd-numbered cycles) or PI-Sce I (for evennumbered cycles) can cleave those background plasmids and retains the intact target recombinant plasmid. This is an important step to enrich and recover the target recombinant plasmid. 10. In order to increase the electro-transformation efficiency, the plasmids dissolved in buffer should be desalted by dialyzing against 1/3 TE using the dialysis membrane Millipore (Cat. VSWPO4700) at 4
C for ~0.5–1 h. The voltage of electroporation parameter is ~1600–1650 V/1 mm and other parameters and operation is according to the manufacturer’s

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instruction. Heat-shock transformation for large plasmids may be of lower efficiency. 11. If few colonies are produced on the double-antibiotic plates, pool all the colonies into 2 ml liquid LB containing 25 μg/ml Kan and 15 μg/ml Chl (for odd-numbered cycles) plus final 0.5 mM IPTG (if pYL0380/1300H are used, do not add IPTG; see Note 2), and culture at 37
C for ~6 h for minipreparation of the mixed plasmids. For even-numbered assembly cycles, use LB supplemented with 25 μg/ml Kan and 70 μg/ml Amp. 12. According to the manufacturer’s instructions of the Gateway BP reaction, longer incubations time (~4–6 h or overnight) are recommended for genes 5 kb to increase the yield of colonies. 13. Due to the existence of homologous recombination system in A. tumefaciens, when multigene vectors contain some genes or fragments with the homologous sequences, the multigene plasmids may be unstable and change structure by possible recombination reaction. When the structural instability of multigene plasmids occurs in one agrobacterium strain (e.g., EHA105), it is recommended to try several different strains (e.g., LBA4404, GV3101, or AGL1). Only structurally stable plasmids in A. tumefaciens can be used for further plant transformation. 14. Due to using pollen-specific promoter PV4 to drive Cre expression, the marker excision occurs only in pollen but not in eggs. Thus, T1 plants have only heterozygotes for the Cre/loxPmediated marker excision (two PCR fragments).

Acknowledgments This study is supported by grants from the National Natural Science Foundation of China (31771740; 31000698) and the Ministry of Agriculture of China (2016ZX08010001; 2016ZX08009002). References 1. Farre´ G, Blancquaert D, Capell T, Van Der Straeten D, Christou P, Zhu C (2014) Engineering complex metabolic pathways in plants. Annu Rev Plant Biol 65:187–223. https://doi. org/10.1146/annurev-arplant-050213035825 2. Farre´ G, Twyman RM, Christou P, Capell T, Zhu C (2015) Knowledge-driven approaches for engineering complex metabolic pathways in plants. Curr Opin Biotechnol 32:54–60.

https://doi.org/10.1016/j.copbio.2014.11. 004 3. Pouvreau B, Vanhercke T, Singh S (2018) From plant metabolic engineering to plant synthetic biology: the evolution of the design/ build/test/learn cycle. Plant Sci 273:3–12. https://doi.org/10.1016/j.plantsci.2018.03. 035 4. Dafny-Yelin M, Tzfira T (2007) Delivery of multiple transgenes to plant cells. Plant Physiol

TransGene Stacking II Vector System for Plant Metabolic Engineering and. . . 145:1118–1128. https://doi.org/10.1104/ pp.107.106104 5. Bock R (2013) Strategies for metabolic pathway engineering with multiple transgenes. Plant Mol Biol 83:21–31. https://doi.org/ 10.1007/s11103-013-0045-0 6. Tzfira T, Tian GW, Lacroix B, Vyas S, Li J, Leitner-Dagan Y, Krichevsky A, Taylor T, Vainstein A, Citovsky V (2005) pSAT vectors: a modular series of plasmids for autofluorescent protein tagging and expression of multiple genes in plants. Plant Mol Biol 57:503–516 7. Petersen LK, Stowers RS (2011) A Gateway MultiSite recombination cloning toolkit. PLoS One 6:e24531. https://doi.org/10. 1371/journal.pone.0024531 8. Shih PM, Vuu K, Mansoori N, Ayad L, Louie KB, Bowen BP, Northen TR, Loque´ D (2016) A robust gene-stacking method utilizing yeast assembly for plant synthetic biology. Nat Commun 7:13215. https://doi.org/10.1038/ ncomms13215 9. Collier R, Thomson JG, Thilmony R (2018) A versatile and robust Agrobacterium-based gene stacking system generates high-quality transgenic Arabidopsis plants. Plant J 95:573–583. https://doi.org/10.1111/tpj.13992 10. Lin L, Liu YG, Xu X, Li B (2003) Efficient linking and transfer of multiple genes by a multigene assembly and transformation vector system. Proc Natl Acad Sci U S A 100:5962–5967 11. Liu YG, Shirano Y, Fukaki H, Yanai Y, Tasaka M, Tabata S, Shibata D (1999) Complementation of plant mutants with large genomic DNA fragments by a transformationcompetent artificial chromosome vector accelerates positional cloning. Proc Natl Acad Sci U S A 96:6535–6540 12. Liu YG, Liu H, Chen L, Qiu W, Zhang Q, Wu H, Yang C, Su J, Wang Z, Tian D, Mei M (2002) Development of new transformation competent artificial chromosome vectors and rice genomic libraries for efficient gene cloning. Gene 282:247–255 13. Zhu Q, Yu S, Zeng D, Liu H, Wang H, Yang Z, Xie X, Shen R, Tan J, Li H, Zhao X, Zhang Q, Chen Y, Guo J, Chen L, Liu YG (2017) Development of “Purple Endosperm Rice” by engineering anthocyanin biosynthesis in the endosperm with a high-efficiency transgene

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stacking system. Mol Plant 10:918–929. https://doi.org/10.1016/j.molp.2017.05. 008 14. Zhu L, Qian Q (2017) Development of “Purple Endosperm Rice” by engineering anthocyanin biosynthesis in endosperm: significant breakthrough in Transgene Stacking System, new progress in rice biofortification. Chin Bull Bot 52:539–542. https://doi.org/10. 11983/CBB17126 15. Fang X, Mao Y, Chen X (2018) Engineering purple rice for human health. Sci China Life Sci 61:365–367. https://doi.org/10.1007/ s11427-017-9157-7 16. Zhu Q, Zeng D, Yu S, Cui C, Li J, Li H, Chen J, Zhang R, Zhao X, Chen L, Liu YG (2018) From golden rice to aSTARice: bioengineering astaxanthin biosynthesis in rice endosperm. Mol Plant 11:1440–1448. https://doi. org/10.1016/j.molp.2018.09.007 17. Chen WC, Lu S (2018) From golden rice to aSTARice, more than just two steps forward in a pathway. Sci China Life Sci 61. https://doi. org/10.1007/s11427-018-9426-2 18. Ma X, Zhang Q, Zhu Q, Liu W, Chen Y, Qiu R, Wang B, Yang Z, Li H, Lin Y, Xie Y, Shen R, Chen S, Wang Z, Chen Y, Guo J, Chen L, Zhao X, Dong Z, Liu YG (2015) A robust CRISPR/Cas9 system for convenient, high-efficiency multiplex genome editing in monocot and dicot plants. Mol Plant 8:1274–1284. https://doi.org/10.1016/j. molp.2015.04.007 19. Chen L, Wang F, Wang X, Liu YG (2013) Robust one-tube Ω-PCR strategy accelerates precise sequence modification of plasmids for functional genomics. Plant Cell Physiol 54:634–642. https://doi.org/10.1093/pcp/ pct009 20. Chen W, Zeng D, Shen R, Ma X, Zhang Q, Chen L, Liu Y-G, Zhu Q (2016) Rapid in vitro splicing of coding sequences from genomic DNA by isothermal recombination reactionbased PCR. Biotechnol Biotechnol Equip 30:864–868. https://doi.org/10.1080/ 13102818.2016.1191374 21. Zhu Q, Yang Z, Zhang Q, Chen L, Liu Y-G (2014) Robust multi-type plasmid modifications based on isothermal in vitro recombination. Gene 548:39–42. https://doi.org/10. 1016/j.gene.2014.07.004

Chapter 3 Morphogenic Regulators and Their Application in Improving Plant Transformation Samson Nalapalli, Meral Tunc-Ozdemir, Yuejin Sun, Sivamani Elumalai, and Qiudeng Que Abstract Generation of plant lines with transgene or edited gene variants is the desired outcome of transformation technology. Conventional DNA-based plant transformation methods are the most commonly used technology but these approaches are limited to a small number of plant species with efficient transformation systems. The ideal transformation technologies are those that allow biotechnology applications across wide genetic background, especially within elite germplasm of major crop species. This chapter will briefly review key regulatory genes involved in plant morphogenesis with a focus on in vitro somatic embryogenesis and their application in improving plant transformation. Key words Totipotency, Plant morphogenesis, Morphogenic regulators, Morphogenic genes, Apical meristem, Somatic embryogenesis, Plant transformation

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Introduction The term totipotency was coined by the animal cell biology expert Thomas Hunt Morgan to explain the ability of a cell to travel down different developmental trajectories and its potential to form all the cell types in the adult organism [1]. In plant biology, totipotency is now broadly defined as the genetic potential of a plant cell to produce the entire plant. One of the most fundamental questions in plant development is the molecular mechanism underlying the induction of totipotency and transition from a differentiated state to become totipotent cells. In plant tissue culture, an explant obtained from selected parts of a plant is grown in vitro to form various structures in the presence of auxinic herbicide 2,4-D and other nutrient factors [2] (Fig. 1). An unorganized mass of cells called callus is propagated in culture medium with mineral nutrients, vitamins and plant growth regulators that promote cell division and growth. The cells in callus tissue are totipotent because it is

Anindya Bandyopadhyay and Roger Thilmony (eds.), Rice Genome Engineering and Gene Editing: Methods and Protocols, Methods in Molecular Biology, vol. 2238, https://doi.org/10.1007/978-1-0716-1068-8_3, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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Fig. 1 Pictorial representation of in vitro plant morphogenesis. (a) Dedifferentiation—initial acceleration of cell division in an isolated explant lead to formation of undifferentiated cell mass called callus. (b) Embryo development through a well-organized sequence of cell division, enlargement and differentiation (c) organ development such as shoot (c1) or root (c2) or both (c3) through organized cell division, enlargement, and differentiation. (d) Well-established in vitro plantlets

possible to regenerate these cells into plants under specific conditions using plant growth regulators or environmental factors such as light, temperature, and humidity [3, 4] (Fig. 1). Unlike animal cells, plant cells show a high degree of developmental pliability and can be readily induced to regenerate new tissues or organs (pluripotency) and even embryos (totipotency) from in vitro-cultured explants [5, 6]. Somatic embryogenesis is a type of plant totipotency in which embryos are induced to form on vegetative explants usually in response to exogenous hormones, especially auxins, or stress treatments [2]. Somatic embryogenesis was first demonstrated in carrot tissue culture [5, 7] and it is extensively used as a clonal propagation tool in biotechnology applications [8–10]. The tissue culture requirements for somatic embryo induction are well known [11]. For embryo formation

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from embryogenic callus, cytokinin, ABA and stress factors in combination with a reduced level of auxin are usually used [2, 12]. In major crop species including rice (Oryza sativa), maize (Zea mays), wheat (Triticum aestivum), sorghum (Sorghum bicolor), sugarcane (Saccharum officinarum), soybean (Glycine max), and cotton (Gossypium hirsutum) remarkable progress has been made by manipulating all facets of tissue culture process to achieve high rate of success in obtaining transgenic events. The refinement of tissue culture conditions has enabled highly efficient genetic transformation of crop plants, particularly monocots, using both particle bombardment and Agrobacterium-mediated transformation gene delivery methods [13]. The preparation of transformation explants has also become simpler with the advancement of technology. For example, in maize transformation target cells have progressed from protoplasts [14–16], to cells in liquid suspension [17–19], and then to embryogenic callus [20, 21] and scutellar cells of freshly isolated immature embryos [22–24]. Immature embryos remain as the preferred target tissues for maize and wheat transformation in most labs. However, other tissues have been studied extensively as transformation targets as well, for example, leaf bases of maize, rice and wheat [25–27], immature inflorescences of sorghum, wheat, rice, tritordeum, and maize [28–33], apical or nodal meristems of maize [34] and regenerable callus from mature seeds-derived embryos in rice [35]. These studies relied heavily on the use of plant growth regulators in the culture media to produce either embryogenic callus or multiple shoot meristems. There were only a few reports of successful generation of transformants from differentiated cells of mature maize explants (e.g. mature embryos or leaf segments) by directly stimulating dedifferentiation and subsequent callus formation [36]. However, this situation has changed recently with the use of morphogenic factors that promote somatic embryogenesis and transformation [36–38]. This chapter will briefly discuss the molecular basis of plant morphogenesis during somatic embryogenesis and the use of genes encoding transcriptional regulators of morphogenesis in improving plant transformation.

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Regulation of Morphogenesis Organ patterning is the arrangement of different cell types and tissues aided by positional and developmental cues that function in a dose- and context-dependent manner and include hormones, short peptides, transcriptional regulators, and microRNAs [39]. An early plant tissue culture study revealed the crucial role of auxin and cytokinin in regulating plant morphogenesis [40]. Auxin and cytokinin balance plays a critical role in meristem formation, stem cell maintenance, and cell differentiation [41]. Auxin and cytokinin cross talk also regulates de novo organ regeneration; alternative

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induction of de novo shoot organogenesis or somatic embryogenesis from in vitro cultures is modulated by the ratio between auxin and cytokinin in the medium [42]. In the shoot apical meristem, cytokinin promotes proliferation, whereas auxin guides organ primordium formation [43]. In contrast, in root apical meristem, auxin is the key hormone regulating meristem formation, whereas cytokinin controls cellular differentiation [41]. Cytokinin influences auxin-induced root apical meristem regeneration via regulation of PIN-mediated auxin polar transport, thus the functions of cytokinin in shoot and root regeneration are different in morphogenesis [44]. Recent reports showed that egg cell–specific expression of BABY BOOM (BBM) in zygotes is sufficient for the induction of fertilization-independent generation of haploid plants; thus, BBM plays a critical role in activating initial cell division and proliferation following normal zygote formation [45, 46]. During embryo development meristem formation and maintenance WUSCHEL (WUS) family members play essential roles in plant morphogenesis; the plant specific WUS protein and its related WUS homeobox (WOX) family members are involved in the de novo establishment of the shoot stem cell niche, stem cell maintenance, embryonic patterning, and organ identity determination [47]. There are fifteen WOX family members in Arabidopsis belonging to three subclades: the WUS clade, the intermediate clade and the ancient clade [47]. Both shoot and root meristem homeostasis are controlled by the WUS/WOX/CLAVATA(CLV) signaling pathways [41]. It is possible that some WOX members have overlapping functions. For example, both WUS and WOX5 are expressed in the respective organizing-center cells of the shoot and root apical meristems to maintain stem-cell function [48]. The spatial induction of the WUS gene plays an important role in shoot apical meristem (SAM) establishment and shoot regeneration that is dependent on the spatiotemporal auxin gradient and a cytokinin response [49]. The expression of the WUS gene defines the organizing center (OC) in SAM and the WUS protein acts as a nonautonomous signal to maintain stem cells by activating CLV3 expression [41]. However, CLV3 in conjunction with its CLV1/ CLV2 receptor kinase complex leads to downregulation of WUS. Thus, WUS and CLV3 form a feedback gene regulatory network [50]. Cytokinin signaling in Arabidopsis is regulated by two types of Arabidopsis Response Regulators (ARRs) that have opposite roles, where the type-A ARRs act as negative regulators and the type-B ARRs as positive regulators of the cytokinin response [51]. Interestingly, WUS represses the expression of type-A ARRs, thus promoting its own expression by sensitizing the OC [41]. During plant shoot regeneration from callus WUS-positive cells mark the shoot progenitor region [51]. In a cytokinin-rich environment the epigenetic marks associated with the repressive histone

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methylation, H3K27me3, is removed at the WUS locus in a cell cycle–dependent manner [51]. The removal of H3K27me3 modification and the resulting open chromatin structure made the WUS locus accessible by the type-B ARRs (ARR1, ARR2, ARR10, and ARR12) for spatial activation of WUS expression through type-B ARRs’ binding with microRNA165/6-targeted HD-ZIP III transcription factors [51]. WUS is synthesized in the rib meristem, then migrates and accumulates at lower levels in adjacent cells, but its N-terminal DNA binding domain along with the homodimerization sequence located in the central part of the protein inhibits WUS from spreading excessively [52]. The SAM is dynamically partitioned into symplasmic fields with closed plasmodesmata at specific locations in the proliferating cellular matrix while morphogens and transcription factors are exchanged via plasmodesmata between adjacent symplasmic fields and ligand–receptor interactions [53]. In order to explain the spatial locations and dynamics of the expression domains of WUSCLV3 regulatory network, theoretical models have been proposed to describe different aspects of the stem cell regulatory network in SAM. For example, a reaction diffusion mechanism was proposed in which an activator induces WUS expression [54]. This reaction diffusion model is able to organize the WUS expression domain and also predicts the dynamical reorganization and the spatial expansion of the WUS domain resulting from the removal of the CLA3 signal [54]. Later, two models (interference and a more parsimonious loss-of-signal hypothesis) based on receptor and ligand turnover, interactions, and signaling were also proposed to explain the WUSCLV3 feedback network including two receptor pathways for predicting phenotypes in both wild type and six CLV1 receptor mutants [55].

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Genes Involved in In Vitro Somatic Embryogenesis Somatic embryogenesis occurs naturally during apomixis in some cereals [56] and plantlet formation from leaves of certain Kalanchoe species [57]. The in vitro somatic embryogenesis system is often used to study gene regulation because somatic embryo induction, formation and development processes can be controlled by the exogenous application of synthetic plant hormones and stress treatments [2]. It is also a great model system for studying early plant development [58], identifying critical genes involved in embryogenesis [59], and mapping gene regulatory networks [60]. There are several clear advantages in using somatic embryogenesis for studying gene regulation since the induction conditions can be applied relatively uniformly to large number of cells. Also, embryos at different developmental stages can be easily identified and collected for gene expression studies. Embryogenesis from somatic

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cells progresses through several stages: (1) induction and acquisition of totipotency competence (dedifferentiation), (2) maintenance of totipotency (embryogenic status), (3) somatic embryo formation (differentiation), and (4) embryo maturation and desiccation. Each of these steps involves perception of external cues and cellular morphogenic signals that result in reprogramming of gene expression regulation at both global chromatin and local gene levels (Fig. 2). Many studies have been carried out to identify proteins and genes expressed during somatic embryogenesis (reviewed by Altamura [61], Elhiti et al. [62], Hand and Koltunow [63], Rose and Nolan [59], and Zimmerman [58]). The earliest studies mainly identified some high abundance transcripts and proteins such as the carrot embryogenic cell culture protein, ECP31, for marking embryo development stages [64]. However, most of these genes have no direct roles in signal transduction or gene regulation. Over the last 20 years, the advent of more powerful molecular, genetic, and genomic technologies has enabled the identification of key genes involved in the regulation of somatic embryogenesis [62]. In an effort to discover differentially expressed genes that mark the transition of somatic cells into competent embryogenic cells in established suspension carrot cell cultures, two genes were identified: one encodes for the Lipid Transfer Protein (LTP), a previously identified marker gene for embryogenic carrot cell cultures and another gene encodes for a leucine-rich repeat (LRR) receptor kinases named Somatic Embryogenesis Receptor Kinase (DcSERK) that marks the first appearance of competent cells during hypocotyl activation [65]. Subsequently, the Arabidopsis homolog AtSERK1 was also found to be highly expressed during embryogenic cell formation in culture and during early embryogenesis [66]. The overexpression of AtSERK1 led to 3- to 4-fold increase in the efficiency of somatic embryo initiation in calli derived from transformed seedlings when they were placed on 2,4-D media [66]. These results show that an increased AtSERK1 level is sufficient to confer and/or maintain embryogenic competence in culture [66]. 3.1 Baby Boom (BBM) and BBM-like (BBML) Genes

A key regulatory factor of somatic embryogenesis, Baby Boom (BBM) was discovered in studies identifying genes that are upregulated during the microspore embryogenesis in Brassica napus [37]. BBM shows sequence homology to a family of APETALA2 (AP2)/Ethylene Response Factor (ERF) transcriptional factors that play an important role in meristem cell fate and organ identity determination [37]. Remarkably, overexpression of BBM in Arabidopsis and Brassica led to spontaneous formation of somatic embryos and cotyledon-like structures on seedlings in the absence of any exogenous hormone in both native and heterologous species [37, 60]. This result suggests that BBM is a key regulator governing

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Fig. 2 Outline of molecular mechanism in plant morphogenesis. Phytohormones (a: shown as yellow gears) are signaling molecules that transduces via a number of transcription factors (TF) (b: shown in green hexagon; blue hexagon); Some of them have a dual role of TF and coregulators. These transcription factors play a pivotal role in coordinated fashion to direct cell division, growth, and organ differentiation. ARFs and ARRs (C: shown in green gears) are transcriptional factors with a coregulatory role in primary response of organ development. ARFs have a major role in auxin regulation, while ARRs in cytokinin regulation favor organogenesis. TFs work alone or with other proteins in complex to regulate expression of effectors (d: shown in purple box). Temporal and spatial expression of these morphogenic genes results in either embryonic fate to form embryogenic callus or meristem fate to evoke shoot or root. PKL facilitates the progression of embryo development by preventing the cell to reenter embryogenesis. H3K27me2/3 and H3K9me2/3 are epigenetic marks associated with transcriptional repression, whereas H3K36me3 and H3K4me3 promote transcriptional activation

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transition from differentiated somatic cells to proliferating embryogenic cells. In Arabidopsis, AtBBM belongs to a small clade of eight AP2-like transcriptional factor genes including AINTEGUMENTA (ANT) and six other AINTEGUMENTA -like (AIL) genes: AIL1, PLETHORA1 (PLT1), PLT2, AIL6/PLT3, CHOTTO1 (CHO1)/ EMBRYOMAKER(EMK)/AIL5/PLT5, and PLT7 [60, 67]. Ectopic expression of another member of the AIL subgroup, AIL5 or EMBRYOMAKER (AtEMK), produced light-green embryo-like structures at the tip margin of cotyledons [68]. The calli derived from Arabidopsis lines overexpressing AtEMK also generated many somatic embryos [68]. These results indicate that overexpression of either BBM or AtEMK alone is sufficient to confer embryonic identity to callus cells and both genes play key roles in the developmental transition from somatic to embryonic phase [37, 68]. Another study also showed functional redundancy for somatic embryogenesis among other Arabidopsis BBM-like members in that another AIL gene, PLT2, also regulates LAFL gene expression [60]. The level of morphogenic factors also influences the outcomes of the morphogenesis as it has been shown that high BBM/PLETHORA (PLT2) dose induces embryogenesis, but a lower dose induces organogenesis, and the lowest dose inhibits differentiation in Arabidopsis [60]. Interestingly, molecular dissection of the single dominant locus controlling apomixis in a wild grass species Pennisetum squamulatum, apospory-specific genomic region (ASGR), revealed that it contains multiple copies of PsASGR-BABY BOOM-like (PsASGRBBML) gene, a member of the BBM-like subgroup of APETALA 2 transcription factors [46]. The introduction of PsASGR-BBML genomic sequence or PsASGR-BBML cDNA under the control of a heterologous egg cell–specific promoter as a transgene into maize, rice and pearl millet also promotes haploid embryo formation without fertilization [46, 69]. A recent report also showed that the egg cell–specific expression of rice BBM1, a BBM- like gene in rice zygotes, is sufficient for the induction of fertilizationindependent generation of haploid plants [45]. Therefore, the BBM family members serve as the key regulatory switches in both somatic and zygotic embryogenesis across different plant species. 3.2 Wuschl (WUS) and WUS Homeobox (WOX) Genes

Another important regulator that promotes formation of embryogenic callus and subsequent somatic embryos from various vegetative tissues, including zygotic embryos independent of any external plant hormones, is the homeodomain transcription factor WUS [38]. It is not clear if WUS and BBM promote establishment of embryogenic competence through the same signaling pathway or if they activate separate gene regulatory pathway of embryogenesis. However, their functions are additive in maize, where expression of both ZmBBM and ZmWUS2 is required for efficient production of calli and somatic embryos from immature embryos of elite lines; even though constitutive expression of ZmBBM alone leads to

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increased callus formation in many but not all genotypes [36]. Interestingly, overexpression of the WOX members from wheat and rice, TaWox5 and OsWox5 respectively, increased transformation frequency in many recalcitrant elite varieties of wheat and maize without the help of BBM [70]. Surprisingly, the ectopic overexpression of TaWox5 and OsWox5 under the control of a strong constitutive maize ubiquitin promoter shows no negative effects and abnormal phenotypes typically associated with WUS overexpression [70]. 3.3 MYB118 and MYB115

The MYB118 gene can also induce the vegetative to embryonic transition and the formation of somatic embryos from root explants. The MYB118 overexpression also upregulates LEAFY COTYLEDON 1 (LEC1) expression level but not of LEC2, that is independent of WUS [71]. Interestingly, MYB118 expression level is not enhanced in the pickle (pkl) mutant in which embryonic traits are expressed after germination, suggesting that the MYB118 is not directly regulated by the PKL locus which encodes a CHD3 chromatin-remodeling factor and regulates the transition from embryonic to vegetative development [71, 72]. MYB118 belongs to a small subgroup of R2R3-type MYB transcription factor with six members [71], and inducible overexpression of MYB115, the most closely related homolog of MYB118, leads to a similar phenotype as MYB118 overexpression [71], while continuous overexpression of both MYB118 and MYB115 causes complete arrest of plant vegetative growth and turns plantlets into callus-like structures [71].

3.4 LEC and Related Genes

Because genes involved in somatic embryogenesis also play critical roles during zygotic embryo development, studies with zygotic embryo defect mutants led to discovery of several important genes that also regulate somatic embryogenesis [73–75]. In Arabidopsis, loss-of-function mutations in LEC1, LEC2, and FUSCA3 (FUS3) genes show striking defects in both embryo identity and seed maturation processes [76, 77]. LEC1 has significant sequence similarity to the HAP3 (Heme Activator Protein) subunit of the CCAAT binding transcription factor subunit B (CBF, also known as NF-YB) that is highly conserved among eukaryotes [73], whereas LEC2 gene encodes a B3 domain transcription factor involved in binding to a core DNA cis-element (CATG) called RY motif [78]. Overexpression of both the LEC1 and LEC2 genes individually is sufficient for induction of somatic embryo formation on plant vegetative tissues, thus LEC1 and LEC2 are also central regulators that act high in the regulatory hierarchy that controls embryogenesis [73, 78]. Another LEC locus FUS3 encodes a transcriptional factor with a conserved B3 domain with high homology to LEC2, and it is also essential for somatic embryo induction [74]. FUS3 protein has a high sequence similarity in its

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B3-domain with ABI3 (Abscisic Acid Insensitive 3) in Arabidopsis [79]. LEC1 controls the expression of FUS3 and ABI3 which regulate seed maturation and storage protein accumulation [80] and it binds directly to the B2-domain containing transcription factor LEC2 to control gene expression [81]. In Arabidopsis, LEC and related genes are collectively referred to as the LAFL (LEC1/LEC1-LIKE [L1L], ABSCISIC ACID [ABA] INSENSI TIVE 3 [ABI3], FUSCA3 [FUS3] and LEC2) network [82]. During normal plant embryo development, the repression of the LEC1 regulatory network is mediated by the VP1/ABI3-LIKE (VAL) genes encoding B3 domain-containing proteins [83]. Mutant val1 which is defective in VAL1 (VP1/ABI 3-LIKE) shows a pkllike phenotype, the val1 val2 double mutant produces somatic embryo-like structures around root and apical meristem regions [83]. Expression of the LEC genes are upregulated in val1 val2 double mutant, thus, VAL factors may function as transcriptional repressors of the LAFL network genes in conjunction with PKL or related factors [83]. LEC1 is an NF-Y (for Nuclear Factor Y) transcription factor and also known as NF-YB9 [84] which interacts with NF-YA, and NF-YC subunits to form heterotrimeric NF-Y complex [83, 85]. In Arabidopsis, there are ten members of NF-YA gene family and several of them, NF-YA1, 5, 6, and 9, play a positive regulatory role in embryogenesis because their overexpression in seedlings is sufficient to induce the formation of somatic embryos from the vegetative tissues [85]. Interestingly, overexpression of LEC1 results in up-regulation of NF-YA1, NF-YA5, and NF-YA9, but not NF-YA6 [85], indicating multiple pathways, complexes or roles for this gene family. 3.5 AGAMOUS-like 15 (AGL15) and AGL18

Several other genes important for zygotic embryo development have also been shown to promote somatic embryo formation. AGAMOUS-Like 15 (AGL15), a MADS domain transcriptional factor, which is involved in zygotic embryo development, is another important regulator for somatic embryo production [86, 87]. Ectopic overexpression of AGL15 promotes production of secondary somatic embryos from cultured zygotic embryos and germinated seedlings in Arabidopsis [86]. Based on the analysis of phenotypes and culture conditions, it is suggested that AGL15 acts primarily on the maintenance of embryonic mode or support of its development, rather than a change in identity [86]. The important role of AGL15 in somatic embryogenesis is further supported by the reduced ability of its loss-of-function mutants to produce somatic embryos [87]. Interestingly, a loss-of-function mutant of a closely related family member, AGL18, also shows decreased ability to produce somatic embryos [87]. The soybean ortholog of AGL15, GmAGL15, enhances somatic embryo formation when ectopically expressed in soybean, suggesting that GmAGL15 also plays a similar role in soybean somatic embryo formation [87].

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3.6 Somatic EmbryoRelated Factor 1 (SERF1)

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In an attempt to identify the genes upregulated by ethylene, an AP2/ERF transcription factor family member, Medicago truncatula Somatic Embryo-Related Factor 1 (MtSERF1) was discovered [88]. MtSERF1 is strongly expressed in the globular somatic embryo and in a small group of cells in the developing shoot meristem of the heart-stage embryo. RNAi knockdown of MtSERF1 inhibits somatic embryo formation in M. truncatula [88]. In Arabidopsis, AGL15 transcriptional factor binds directly to the promoter of At5g61590 gene which encodes a protein with high homology with MtSERF1 [89]. At5g61590 gene is required for AGL15-mediated somatic embryogenesis and overexpression of AGL15 upregulates the level of At5g61590 transcript [89]. Interestingly, the promoter of MtSERF1 has ethylene, auxin and cytokinin-response elements as well as binding sites for WUS [2]. This implies that WUS operates in cross roads of ethylene, auxin and cytokinin. The identification of the above key regulators has greatly advanced our understanding of the underlying molecular mechanism of somatic embryogenesis and enabled scientists to develop new and more efficient ways for plant transformation. However, we still do not know all the details of the pathways and regulatory networks in which these regulators function in somatic embryogenesis (Fig. 2). Recent studies showed that BBM induces somatic embryogenesis by directly activating the LAFL network transcriptionally, thus placing BBM upstream of other major regulators of plant embryo identity and totipotency [60]. FUS3 and LEC1 are essential for this process, but LEC2 and ABI3 quantitatively regulate BBM-mediated somatic embryogenesis [60]. The effect of BBM on somatic embryogenesis is dose- and context-dependent, and the context-dependent phenotypes are associated with differential LAFL expression [60]. In tobacco, inducible ectopic expression of Arabidopsis LEC2 causes somatic embryo formation and plant regeneration [90]. LEC2 overexpression induces upregulation of key embryo development regulators including MADS-box protein 9, L1L (LEC1-like), SERK1, and also genes involved in auxin signaling, transport and metabolism such as ARF8 and ARF5, auxin efflux facilitators PIN1 and PIN2, CKX (cytokinin oxidase/dehydrogenase) [90]. Besides LEC2 directly activates AGL15 which enhances the somatic embryogenesis from zygotic embryos and IAA30 which encodes an auxin signaling protein that is enriched in the quiescent center of Arabidopsis root apical meristems [91]. The auxin biosynthetic genes YUC2 and YUC4 are also upregulated by LEC2 [92]. In brief, all these studies show a direct link between auxin and LEC2 in somatic embryogenesis (Fig. 2).

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Epigenetic Regulation of Somatic Embryogenesis Somatic embryogenesis is also controlled at global chromatin level. For example, phenotypes of a loss-of-function mutant of chromatin negative regulator gene PKL (PICKLE) [72] are suppressed in the presence of gibberellin, but enhanced by gibberellin biosynthesis inhibitor uniconazole-P [93, 94]. PKL may act as a master negative regulator for the LEC1, LEC2, and FUS3 genes [72, 95] because the loss-of-function mutation pkl displays phenotypes similar to LEC1 overexpression. Thus, PKL serves as a component of a gibberellin- modulated developmental switch to prevent reexpression of the embryonic developmental state during germination [95]. The Trithorax Group (TrxG) and Polycomb group (PcG) factors are competing epigenetic regulators that are critical for maintaining transcription patterns at developmental regulatory loci through chromatin organization [96]. The SET DOMAIN GROUP 2 (SDG2) and ARABIDOPSIS HOMOLOG OF TRI THORAX1 (ATX1/SDG27) are two H3K4 histone methyltransferase TrxG factors. SDG2-mediated H3K4 methylation is required for proper Arabidopsis root growth and development [97], while ATX1/SDG27 is required for cell production, patterning, and morphogenesis in root development [98]. Another TrxG factor, SDG8 is the major H3K36me3 methyltransferase in Arabidopsis and regulates shoot branching [99]. Chromatin marks deposited by PcG complexes result in a repressive state of the transcription [100] contrary to what TrxG factors do. The PcG complexes repress their target genes partially by catalyzing H3K27me3 in euchromatic domains with protein-coding genes especially transcription factors and genes involved in developmental transitions of plants [101, 102]. Recent study shows that the spatial signaling pattern of phytohormones particularly cytokinin in the meristem dome help to stabilize WUS protein through the acidic domain of the WOX homeobox [103](Fig. 2). The histone marks associated with repressive chromatin, H3 lysine 9 dimethylation (H3K9me2) and H3K27me3 are mutually exclusive and can replace one another in a locus-specific manner [101]. Histone H3 methylation plays an important role in embryo development; WOX4 is regulated by the repressive mark H3K9me2, whereas LEC1 and BBM1 are epigenetically regulated by H3K27me3 [104]. Besides, DNA METHYLTRANSFERASE1 (MET1) represses shoot regeneration by inhibiting the WUS expression and this is regulated by the cytokinin-induced cell cycle [105]. A report on the expression and DNA methylation patterns of BBM and WUS in in vitro cultures of Boesenbergia rotunda shows that the highest level of expression of BBM is observed in embryogenic callus, whereas WUS is most highly

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expressed in meristematic block tissue followed by embryogenic callus; embryogenic callus samples have the lowest levels of DNA methylation at CG, CHG (where H is A, C, or T) and CHH contexts of WUS [106]. Thus, there is a negative correlation between DNA methylation at the CG and CHG contexts and the expression levels of BBM and WUS [106].

5

Application of Morphogenic Regulator Genes in Plant Transformation Genetic engineering leverages the totipotency of plant cells to introduce the desired genes into cultured plant cells, tissues or organs, and subsequently regenerate them into fertile plants. This process is widely known as plant transformation, one of the core technologies in agricultural biotechnology industry. The major challenge of applying this technology to crop species is that the transformation frequencies for a wide range of crop species are low and most commercially important varieties or landraces are recalcitrant to transformation. The initial observations that overexpression of the WUS and BBM genes promoted embryogenesis in Arabidopsis and Brassica [37, 38] sparked efforts of applying those two genes to improve transformation efficiency (Table 1). However, the control of the optimum expression control appears to be the major obstacle for this application. As reported by Boutillier et al. [37], high level expression of BBM driven by both constitutive promoters, cauliflower mosaic virus 35S promoter (pr35S) promoter and sunflower ubiquitin promoter (prUbi) induced pleiotropic phenotypes in Arabidopsis and Brassica seedlings such as pinched or lobed cotyledons and leaves, thickened or callused hypocotyls, formation of ectopic shoots, short roots, callus formation, and anthocyanin accumulation. Ectopic expression of WUS under the control of pr35S in Arabidopsis also caused swollen hypocotyls, shoot-like embryos, enlarged root-tips and abnormal flower structure [38, 107]. Abnormal flower development was also observed in activation tagged wus mutant Arabidopsis lines [108]. Subsequent tests of high level expression of BBM genes in tobacco, sweet pepper and chocolate tree driven by pr35S resulted in pleiotropic phenotypes such as callus formation, swollen cotyledons, leaf rumpling, and male/female sterility [109–111]. Likewise, pr35S driven expression of Arabidopsis WUS gene in cotton massively promoted somatic embryogenesis but significantly inhibited regeneration; the resulting transgenic cotton plants demonstrated characteristic “Wuschel phenotypes” of multiple branches and waffle-curled leaves as observed previously in Arabidopsis [112]. Significant progress in the use of morphogenic genes in plant transformation was accomplished by the use of inducible expression systems to eliminate the negative impacts of constitutive expression of the embryogenesis promoting genes. An elegant construct

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Table 1 Plant morphogenic genes, their biological function and application Gene(s)

Function and application

Target plant(s)

References

AGL15

Embryogenesis, transformation

Arabidopsis, soybean

[86, 87, 89]

AIL

Embryogenesis, organogenesis and Arabidopsis transformation

ANT

Floral meristem, ovule development, embryogenesis

Arabidopsis

[60, 67]

BBM, BBML

Embryogenesis, transformation

Brassica, maize, pearl millet, sorghum, rice, sugarcane, tobacco, sweet pepper, cacao Chinese poplar

[36, 37, 46, 60, 69, 104, 109–111, 113, 115, 116]

CLV

SAM development and maintenance

Arabidopsis, maize, rice, tomato [128, 129]

EMK

Embryogenesis

Arabidopsis

[37, 68]

FUS3

Embryo maturation

Arabidopsis

[60, 80]

GRF5, GRF4GIF1

Growth and development, regeneration, transformation

Sugar beet, soybean, canola, [122, 130] sunflower, maize, wheat, citrus

Lec1, Lec2

Embryogenesis

Arabidopsis, tobacco

[73–75, 77, 78, 80, 81, 90–92]

MYB118/ Embryogenesis MYB115

Arabidopsis

[71, 85]

PKL

Embryogenesis

Arabidopsis

[72, 95]

PLT1, PLT2, PLT3

Shoot and root development, transformation

Arabidopsis

[68]

SERF1

Embryogenesis

Medicago

[88]

SERK

Embryogenesis

Carrot

[65, 66]

STM

Meristem development

Tobacco, tomato, potato, grape

[117]

Val

Embryogenesis

Arabidopsis

[83]

WUS, WOX

Stem cell maintenance, anther and Maize, sorghum, rice, sugarcane, [36, 38, 47, 51, 70, wheat 85, 104, 116, ovule development, 131] embryogenesis and transformation

[67]

design of heat shock-induced removal of pr35S controlled BBM gene expression cassette (pr35S:BBM) was reported [113]. In this study, BBM from Brassica campestris was under the control of pr35S and the FLP recombinase was under the control of Arabidopsis heat shock inducible promoter prHSP18.2. FRT recombination sites

Morphogenic Regulators and Their Application in Improving Plant Transformation

51

flanked the cassette containing the pr35S:BBM and prHSP18.2:FLP expression units. Using this construct, Chinese white poplar tree (Populus tomentosa Carr.) was successfully transformed without abnormal morphological phenotype when the pr35S:BBM cassette was removed upon heat shock induction prior to plant regeneration. In contrast, abnormal phenotypes were observed without removal of the pr35S:BBM cassette [113]. Later on, a steroid induced BBM expression system was developed to successfully transform Arabidopsis leaf tissue [114]. It was reported that Arabidopsis BBM was fused to the ligand-binding domain of the rat glucocorticoid receptor. Without the synthetic steroid dexamethasone, the rat steroid receptor binds to cytoplasmic components such as HSP90. Upon induction with dexamethasone, BBM fusion protein was translocated into the nucleus and triggered the embryogenesis process. Normal plant differentiation and development resumed after removal of the steroid inducer. Transgenic Arabidopsis plants obtained through this approach were fertile with normal seed setting [114]. Transformation of corn, one of the most important cereal crops, by combining BBM and Wuschel2 (WUS2) from maize was reported by DuPont/Pioneer using the desiccation induction system [36]. The reported research used desiccation inducible promoter Rab17 from maize to drive the excision of the BBM and WUS2 genes using the Cre/LoxP recombination system. The synergy of the two embryogenesis promoting factors greatly enhanced the transformation frequency of an array of elite corn inbreds, though overexpression of BBM alone also enhanced the transformation frequencies of several elite corn inbreds. It was also demonstrated that the combined BBM and WUS2 was able to induce embryogenesis directly from mature seeds and leaf from seedlings of maize, sorghum, rice, and sugarcane [36]. An alternative approach is to conduct cotransformation with two separate constructs, each carries prUbi:BBM or nopaline synthase promoter (prNOS):WUS cassette that can be excised by Cre/LoxP-mediated recombination under the control of a desiccation-inducible Rab17 promoter. This approach has resulted in successful transformation of the recalcitrant corn inbred B73 and sorghum P89812 [115]. The inducible expression of BBM and WUS has resolved negative effects on the morphology of the transgenic plants, but it involves additional steps in the transformation protocol with extended timeline and complicated construct design. To address this problem, the use of a simplified expression system for BBM and WUS was reported [116]. In a search to identify promoters that will drive the expression of BBM and WUS with no negative impacts on plants growth and development, these authors tested a suite of different promoters to drive the expression of BBM and kept the prNOS:WUS in the expression cassette. The use of maize phospholipid transferase protein gene promoter (prZmPLTP) for BBM

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expression resulted in formation of somatic embryos. Those embryos subsequently formed fertile plant but T1 seeds of those plants have poor germination rate. Further optimization of the expression cassettes was accomplished by keeping the ZmPLTP promoter to drive the expression of maize BBM and replacing the NOS promoter with a maize auxin inducible gene promoter (prZmXig1). With the use of the expression cassettes with prZmPLPT:ZmBBM and prZmXig1:ZmWUS2, transformation frequency was significantly enhanced without removing these cassettes in transgenic plants. Most importantly, the resulting plants are fertile with normal germination rates [116]. Recently, ectopic delivery of morphogenic factors such as BBM, WUS2 and STM or cytokinin biosynthetic gene IPT was combined with in planta meristem transformation to directly generate transgenic plant lines without tissue culture [117]. It was shown that maize WUS2 in combination with Arabidopsis STM or IPT resulted in the formation of highest number of shoots in diverse dicot plants including tobacco, tomato, potato and grape. In the same report, codelivery of Agrobacterium strains harboring vectors expressing CRISPRCas9 editing system and morphogenic factors led to successful recovery of edited tobacco plant lines using both young seedlings and soil grown plants without selection or tissue culture [117].

6

Perspectives Morphogenic regulators have many practical biotechnological applications including somatic embryogenesis for micropropagation, doubled haploid production and crop transformation. Recent rapid advances in genome editing technologies have reinvigorated the interest to develop efficient crop transformation systems, especially for the need to transform elite germplasm directly so edited variants can be tested in proper genetic background [118– 120]. Overexpression of BBM-WUS2 to enhance transformation efficiency is one of the major developments in plant transformation technology [36, 115, 116]. A recent review provide an excellent insight of how we could use these morphogenic genes to improve recovery and regeneration of transgenic plants [121]. One of the main areas that needs improvement is finding more efficient ways for BBM-WUS transgene removal from the transgenic events to avoid aberrant phenotypes. The use of tissue-specific or inducible expression systems only partly addresses this issue. It should also be possible to place BBM-WUS expression cassettes and trait gene cassette in separate vectors, codeliver them into plant cells, but select for the trait gene vector to recover events only containing trait gene insertion. Conceptually, a cocktail of BBM-WUS proteins can be delivered into plant cells to help somatic embryo formation. If it is done efficiently, it would eliminate the

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need to have BBM-WUS transgene in the transformation vector. This would simplify construction of transformation vectors and maybe further increase transformation efficiency. In addition, transient delivery of morphogenic factors as proteins will enable their broader use in other breeding applications of many crops because the lines created in this fashion will not fall under the scope of GM regulations. For simplification in the use of morphogenic regulator technology some development has been achieved, for example, a recent report describing the use of WOX alone from wheat and rice, TaWox5 and OsWox5 respectively, was able to significantly increase transformation frequency in many wheat and maize recalcitrant elite varieties without the help of BBM and the transgenic plants did not exhibit negative effects and abnormal phenotypes typically associated with WUS overexpression [70]. The use of morphogenic factor technology has so far been focused on species that have an embryogenic pathway of regeneration. In many important dicot crops the most efficient transformation system is organogenic, such as for soybean, cotton and sunflower. Therefore, it remains to be investigated if BBM-WUS can be optimized or other morphogenic factors are required to enable transformation of the wide range of germplasms in these species. The recent report by Maher et al. [117] suggests that WUS, rather than BBM is probably the key morphogenic member for dicot system development. Also, it is encouraging that expression of another plant development regulatory gene AtGRF5 led to high transformation efficiency in a broad range of monocot and dicot plant species [122]. Likewise, Hoerster et al., [123] report that expression of Zm-Wus2 alone driven by maize Pltp promoter (phospholipid transfer protein) with three viral enhancer elements were enough to induce embryogenesis on the scutella tissue of maize immature embryos. The distinctive properties of Pltp promoter shown to be a strong spatiotemporal expression especially in the epithelial layer of scutella tissue and not in the early-stage embryos, meristem, roots, or reproductive tissue [116]. It is also speculated that the WUS protein from transformed epithelial cells could stimulate cell division in neighboring cells leading to induction of somatic embryogenesis transiently. Such phenomenon is now designated as “altruistic transformation” [123]. Such altruistic transformation through transient expression of either hormone genes or selectable markers for the direct production of marker free transgenic events were demonstrated in grapevines [124]. These techniques pave way to an alternative method of enhancing transformation without the integration of morphogenic genes. Although, the use of morphogenic genes immensely improve the efficiency transformation system in number of recalcitrant genotypes and crops; one of the bottlenecks is in generation of healthy

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molecular quality events. Increased concentration of NO3 and the optimal ratio of NH4+ to K+ in the somatic embryo maturation medium had significant effects in improving the phenotype issues with the plantlets derived by this method. The optimal ratio of 1:1 for NH4+/K+ and 20 mM of NO3 during early embryo development help to produce most desirable phenotype. The presence of ABA in the rooting medium help improve the rooted plantlets [125]. Plant morphogenic regulators also have important practical applications in the development of new breeding technologies such as in doubled haploid production to accelerate breeding and in seed production technologies. In some plants, asexual somatic embryogenesis occurs naturally in ovule during apomixis [63] or in leaf cells when Bryophyllum plants are stressed [57, 126]. A recent agricultural breakthrough showed that ectopic expression of BBM gene alone in the egg cell is sufficient for inducing efficient fertilization-independent generation of haploid plants [45, 69]. Combination of genetic control for cell division genes MiMe and morphogenic factor BBM1 or haploid inducer gene MATRILINEAL (MATL) in reproductive organs makes it possible to engineer asexual synthetic apomixis for maintaining heterosis in hybrids through seeds in cereal crops [45, 127]. With efficient somatic embryogenesis and synthetic apomixis it might be possible to convert some vegetatively propagated crops into seed-propagated crops economically.

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Chapter 4 A Rapid Method for Stably Transforming Rice Seeds Sudheer Kumar and Neeti Sanan-Mishra Abstract Plant transformation technology offers ample opportunities for basic scientific and translational research. Several Agrobacterium-mediated plant transformation protocols are available, for transforming rice, through callus initiation and regeneration. The regularly used transformation procedures require time and skilled labor and are limited by the regeneration capabilities of the tissue. Here we describe a simple, robust and tissue culture-independent method for transformation of rice seeds using pCAMBIA-amiR820 as model construct. Plants obtained from the transformed seeds were selected on antibiotic media and tested for transgene integration and expression by molecular techniques. The transgenic seedlings thus produced include a mix of stable transformants and chimeras; however the first generation seeds contained stably integrated transgene. Key words Rice seeds, Transformation, In planta, Artificial microRNA, Agrobacterium tumefaciens

1

Introduction Plant transformation is a scientific approach whereby DNA from any organism is stably inserted into the genome of a species of interest. It has become an inevitable research tool for characterization and functional analysis of a particular gene. It is also a practical tool for improving existing food and fiber crops varieties. Agrobacterium-mediated transformation remains a successful and preferred method for genetic modification of plants. This is due to its high efficiency of transformation, stable integration of T-DNA into chromosomes, minimal rearrangement of transgene and transfer of relatively large segments of DNA in small copy numbers [1, 2]. The Agrobacterium-mediated gene delivery by the tissue culture route is a complex method that requires aseptic conditions, proper media composition, preparation of callus from explant, introduction of DNA by Agrobacterium, selection of transformed callus and regeneration of an intact plant [3–5]. This method is labor-intensive and time-consuming, and often regeneration from transformed callus is a major bottleneck. Moreover, regenerated

Anindya Bandyopadhyay and Roger Thilmony (eds.), Rice Genome Engineering and Gene Editing: Methods and Protocols, Methods in Molecular Biology, vol. 2238, https://doi.org/10.1007/978-1-0716-1068-8_4, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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plants may exhibit somaclonal variations, morphological abnormalities [6–9], genetic instability [10] and reduced fertility [11]. The regeneration-based transformation protocols currently in practice are not attractive, convenient and equally efficient for most of rice cultivars. For rice it is known that most indica genotypes are less amenable to genetic modification as compared to japonica genotypes due to their poor regeneration potential [12]. The direct, in planta transformation with Agrobacterium provides a potential alternative by avoiding the tissue culture and regeneration steps [13]. Here we demonstrate a simple, robust, convenient and efficient protocol for directly transforming rice seeds that can be used for most of rice cultivars.

2

Materials Prepare all solutions using ultrapure deionized water and analytical grade reagents. Prepare and store all reagents at room temperature (unless indicated otherwise). Carefully follow all waste disposal regulations when disposing waste materials.

2.1 For Agrobacterium Transformation

1. Plasmid vector: pCAMBIA1300 and PCAMBIA1302 (Cambia, Australia) that contain kanamycin as plasmid selection marker, hygromycin as plant selection marker, and GFP as reporter gene [14]. 2. Gene of interest: osa-amiRNA820 [14]. 3. Bacterial strains: Escherichia coli DH5α (Invitrogen, Life Technologies, USA), Agrobacterium tumefaciens (LBA4404 and EHA105). 4. Markers: 1 kb ladder, 100 bp plus ladder, low-range ladder (Fermentas International Inc., Ontario, Canada). 5. Kits: Plasmid DNA isolation kit, QIAquick Gel Extraction Kit (Qiagen, Germany).

2.2 For Plant Screening and Selection

1. Plant material: Mature, dehusked seeds of Oryza sativa Pusa Basmati 1 and IR64. 2. Media components: MS salts (Duchefa Biochemie, The Netherlands), LB medium, YEM (yeast extract media) containing Dmannitol, 10%; K2HPO4, 0.5%; yeast extract, 0.4%; MgSO4∙7H2O, 0.2%; NaCl, 0.1%; distilled water, pH 6.8–7.0. 3. Antibiotics: Hygromycin (50 mg/L HiMedia, India), cefotaxime (250 mg/L), kanamycin (50 mg/L), streptomycin (35 mg/L), rifampicin (25 mg/L), and acetosyringone (100 mM). 4. Plant culture media: MS salts with vitamin B5 + 30 g/L sucrose + 0.3 g casein hydrolysate + 2.0 mg/L 2,4-D + 0.5 g proline + 0.3% phytagel, pH 5.8.

A Rapid Method for Stably Transforming Rice Seeds

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Methods

3.1 Agrobacterium Transformation and Culture

1. Mix 2–3 μg of binary vector (pCAMBIA1300-amiR820) plasmid DNA with the Agrobacterium competent cells and keep on ice for 30 min. 2. Freeze the DNA and cell mix in liquid N2 for 1 min. Then incubate at 37  C for 5 min for introduction of plasmid DNA into Agrobacterium. 3. After this, keep the tube on ice for 5 min and add 900 μl of LB media to the tube. Incubate the contents at 28  C, 180 rpm for 4–5 h, to allow the Agrobacterium culture to grow. 4. Centrifuge the contents at 5000 rpm for 5 min. Remove the supernatant and retain the pellet. Resuspend the pellet in 100 μl LB medium and spread this pellet mix on LB agar medium plate which contains the required antibiotics. Incubate at 28  C for 48 h to allow the colonies to appear. 5. Check the transformed colonies for the presence of desired gene of interest by colony PCR. 6. Select a positive colony inoculated in starter culture of 5 ml YEM media containing antibiotics. Incubate at 28  C for 48 h with continuous shaking at 180 rpm (see Note 1). 7. Use the primary culture to inoculate 50 or 100 ml aliquots of YEM secondary culture and allow to grow (see Note 2). 8. Use for agroinfection of the seeds.

3.2 Preparation of Plant Material

1. Select mature, dehusked, and healthy seeds of rice cultivar Pusa Basmati 1 and IR64. 2. Surface sterilize the seeds by washing five times in autoclaved RO water, followed by 70% ethanol for 2 min. 3. Treat with 50% sodium hypochlorite containing 2–3 drops of Tween-20 for 10–15 min with mild shaking at slow speed. 4. Wash the seeds, 7–10 times with sterile water so that residual traces of ethanol or sodium hypochlorite are completely removed (see Note 3). 5. Allow the sterilized seeds to air-dry on autoclaved Whatman paper in aseptic conditions and then use for transformation (Table 1).

3.3 Transformation of Rice Seeds

1. Co-culture the surface sterilized seeds with the Agrobacterium (secondary) cultures supplemented with 100 mM acetosyringone and incubate at 28  C in the dark for 16 h at slow shaking (see Note 4).

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Table 1 Schematic workflow of the protocol

Rice seeds INFECTION

16 h

Agrobacterium tumefaciens 100µM Acetosyringone Axenic conditions, dark

Seeds are blot dried antibiotics) CO-CULTIVATION conditions

Fresh MS medium (without 2-3 days

Dark, under tissue culture

Transferred to selection media SELECTION I

15 days

Hygromycin (50mg/L) Cefotaxime (250mg/L) 28.0°C, ~4.5 klux

Fresh selection media SELECTION II

15 days

Hygromycin (50mg/L) Cefotaxime (250mg/L) 28.0°C, ~4.5 klux

Seedlings in MS liquid media (without sucrose) HARDENING Soil pot SCREENING Transgenic Seed Collection

2. For co-cultivation, blot-dry the co-cultured rice seeds and place on fresh MS medium plates without antibiotics, in the dark under tissue culture conditions (Fig. 1). 3. Allow the seeds to germinate and grow for 2–3 days in the dark, till they are around 2–4 cm in length. 4. Transfer the young seedlings to culture media, supplemented with hygromycin (50 mg/L) and cefotaxime (250 mg/L) and grow under the light/dark cycle in aseptic conditions for 3–4 weeks (see Note 5). 5. Change to fresh antibiotic media plates after 10–15 days to maintain the potency of antibiotics (see Note 6).

A Rapid Method for Stably Transforming Rice Seeds

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Fig. 1 Representative photographs of the various stages of transformation with pCAMBIA1300-amiR820. The first panel represents seeds at 1 day after transformation, the middle panel represents 1-week-old seedlings on selection medium and the last panel represents young seedlings on second selection

6. Transfer the surviving seedlings (10–12 cm in length) to MS liquid media in culture tubes and grow for 2–3 days (see Note 7). 7. Transfer to vermiculite pot for hardening and check the leaf tissue of young seedlings by molecular analysis (see Note 8). 8. After 30 days transfer the plants to soil pots and allow to grow till maturity (see Note 9). 3.4 Screening for Stable Transgenics

The plants grown in pots include stable transformed population of transgenics and/or chimeras. So screening for transgenic seeds forms an essential part of the protocol. 1. Collect the seeds of the putative primary transformants and germinate in presence of antibiotics. The seeds of some plants may not germinate. 2. Selected seedlings growing in presence of antibiotics may be analyzed for the presence and expression of transgene (see Note 8).

4

Notes 1. The antibiotics, rifampicin (25 mg/L), and streptomycin (35 mg/L) can be used for Agrobacterium strain LBA4404 selection and kanamycin (50 mg/L) for binary vector selection. 2. Cell density relative to OD600 values 0.5–0.8 are most suitable for transformation. The optimal cell density needs to be optimized for each construct, Agrobacterium strain used and the rice cultivar. 3. Thorough washing is essential as the residual traces may interfere in subsequent steps. 4. Shaking should be very slow at 30% or 2) can be used to generate short indels, small to larger internal gene deletion, or full-length gene deletion. Sequencing of edited gene is required to confirm in-frame or frameshift mutation at coding sequence of edited gene

(f) Guide target sequence should avoid repetition of bases (>4) and palindromic sequences which can potentially form gRNA secondary structure in vivo. (g) Composition of a guide shall be comparable to that of target genome with 50–65% GC content and the start base can either be “A” or “G” depending on selection of RNA polymerase III promoter that is used to drive the expression of gRNA—“A” for U3 and “G” for U6 (based on transcriptional start site). In case, it is not available in the target sequence, the first nucleotide can also be added to the 50 end of the guide oligonucleotide (as described in the cloning section). (h) The guides can be selected either manually or by using publicly available gRNA designing software tools (http://crispr.dbcls.jp/, http://crispr.hzau. edu.cn/CRISPR2/, http://www.multicrispr.net/ basic_input.html, etc.). We strongly advise use of software design tools for better efficacy and reduced/no off-target effects. 3. SDN1 editing may involve single guide, two guides, or multiple guides (>2) (Fig. 4).

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(a) Single guide: This approach is used for creating short indels which result in either in-frame or frameshift mutation. This is used to target a single gene or a gene family having common domain or high homology. Selection of the gRNA target closer to translational start site results in frameshift mutation that is closer to the N-terminal end of the protein, thereby enhancing the scope of generating strong phenotype for the target gene. (b) Two guides: This is used to create internal gene deletion resulting in a truncated protein or for fulllength gene deletion. It is useful when a specific gene fragment that encodes for a domain, motif, signal sequence, etc., is selected for deletion from the target gene. (c) Multiple guides: This method can be used for following approaches: l

To target a single gene for higher knockout efficiency.

l

Targeting multiple genes which are involved in a common signaling pathway resulting in disruption of the pathway; multiple genes involved in diverse biochemical pathways can also be targeted simultaneously in single experiment (e.g., QTL knockout).

4. SDN2 editing may involve single guide or two guides. (a) Single guide: it can be used for editing single nucleotide or a few spanning a very short DNA fragment. It can be preferred to edit single nucleotide polymorphism (SNP); DSB cut site needs to be very close to the target nucleotide(s). (b) Two guides: it can be used when the editing involves multiple bases spanning a relatively larger DNA fragment. Further, repair template can be of two types: (a) Single-stranded DNA (ssDNA): It can be used for a shorter template (~100–150 bases) with single or multiple edits spanning a shorter DNA fragment. Protected or capped ssOligo may be better suited for acting as repair template. (b) Double-stranded DNA (dsDNA): It is preferred when a larger repair template is used to edit both single and multiple nucleotides. It can be used with single or two gRNAs. DNA can also be edited by “CRISPR base editors” without generating DSB [18, 32, 37–40]. Using this approach, deactivated

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Cas9 protein-gRNA complex is conjugated with specific enzymes which edit the target base without inducing DNA double-stranded breaks. One such study engineered deactivated Cas9-gRNA with cytidine deaminase enzyme to generate cytidine to thymidine substitution [18, 37]. Similarly, adenine base editor has been designed to convert adenine to guanine [38]. Although these are promising technology additions, currently there are limitations to use this approach to edit multiple nucleotides in single experiment. 3.2 Vector Construction

Vector is designed with three major expression cassettes—Cas9, gRNA, and plant selectable marker (for DNA-mediated transformation) (Fig. 5). 1. The vector construction process is outlined in Fig. 6. We have selected rice MS26 gene (Os03g07250.1) as an example to describe editing strategy for SDN1 (nucleotide deletion) and SDN2 (nucleotide substitution) types of genome editing (described in later section). 2. The guiding principle for the vector design follows best practices of vector construction with additional emphasis on the following aspects—duplication of elements should be avoided, cassettes need to be separated by spacer elements to minimize transcriptional interference, and convergent configuration of cassettes is to be avoided. 3. Quality checks in a form of diagnostic restriction digestion, PCR amplification, and sequencing need to be carried out at each step. 4. Different components of vector for plant transformation are cloned by using commercially available CRISPR-specific gene cloning kits or by standard gene cloning procedures [41]. 5. One can use both rice U3 and U6 RNA polymerase III promoters to drive gRNA expression with PolyT (TTTTTT) at 30 end. Streptococcus pyogenes Cas9 (SpCas9) gene was codon optimized for expression in rice cells. Sequences for nuclear localization signal for eukaryotic system were fused at both 50 (SV40) and 30 (VIRD2) ends of SpCas9 gene. Rice codon optimized SpCas9 was expressed with maize ubiquitin promoter and PINII at 30 end as transcription stop signal. 6. Repair template for SDN2 protocol can be synthesized with desired edit(s) and often with additional nucleotide alterations. It is important to note that the repair template should not get cleaved affecting the edited nucleotide(s) by the gRNA that is used to generate DSB in target gene. Template heterogeneity can be maintained by altering few bases employing codon degeneracy—the template should provide only the desired change in protein sequence but may incorporate nucleotide alteration at target DNA sequence. Few nucleotides at seed

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Target trait selection

Target gene selection

Target line selection

Evaluate vector for defined structure and quality criteria by cPCR, digestion QC & sequencing

Meets criteria ?

Target guide design

Sequencing of target gene/region

Vector design (VNTI)

Entry & intermediate vector construction

In-silico/In-vitro off-target screening

No Expression vector construction Yes

QC evaluation of vector by cPCR, digestion & sequencing

Pass?

No

Yes

Handover for transformation

Fig. 5 Vector construction process flow. Key steps in the construction of CRISPR-Cas vectors for plant transformation

sequence (PAM proximal nucleotides of the guide) and “GG” of SpCas9 PAM (NGG) can be selected for this purpose. 7. For double-stranded DNA repair template, the template can be cloned along with gRNA, Cas9, and selectable marker cassettes in a single expression/binary clone. It can be used for both Agrobacterium and biolistic method of transformation. 8. For single-stranded repair template, the oligonucleotide template is co-bombarded along with the binary vector having gRNA, Cas9, and selectable marker cassettes. Please note that currently use of single-stranded template is not possible for Agrobacterium-mediated transformation. 9. The final expression vector shall be sequence verified base by base before proceeding for transformation experiments. 10. Vector construction designing protocol to generate deletion in rice MS26 gene by SDN1 (Fig. 6). (a) Target for single guide was selected based on unique site in rice genome (20 bases gRNA target followed by PAM) (Fig. 6a). (b) OsU6 was selected as promoter to drive gRNA expression along with PolyT tail as transcriptional stop signal.

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Cytochrome P450 (Os03g07250.1)

a

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Cas9-gRNA target

GACGTACGTGCCCTACTCCATGG b.

OsU6 Pro

gRNA

PolyT

Ubi Pro

Cas9

PINII

Ubi Pro

HygZsYellow

PINII

Fig. 6 SDN1 editing of rice MS26 gene. (a) gRNA target sequence in MS26 gene. PAM sequence is underlined. (b) T-DNA schematic of Cas9, gRNA, and plant selectable marker cassettes in a binary vector backbone

SNP ATGGTGACGTACGTGCCCTACTCCATGGGGAGGATGGAG

Met-Val-Thr-Tyr-Val-Pro-Tyr-Ser-Met-Gly-Arg-Met-Glu Repair template 200bp

GGG to TGG

ATGGTGACGTACGTGCCCTACTCCATGTGGAGGATGGAG

Met-Val-Thr-Tyr-Val-Pro-Tyr-Ser-Met-Trp-Arg-Met-Glu Fig. 7 Schematic for generation of SDN2 edits (SNP) in MS26 gene using single guide. Glycine (Gly) is edited to tryptophan (Trp) by single base editing (G to T) from first base in Gly codon GGG to Trp codon TGG. The guide was selected with PAM sequence overlapping target base (SNP edit). Additional bases can be changed in seed sequence using codon degeneracy, thus changing DNA sequence without changing amino acid sequence other than intended target; it may help in stability of the edited allele. Bold TGG indicates PAM, Red G indicates SNP, yellow highlighted sequence is guide target, turquoise indicates the target codon (GGG), and green indicates edited codon (TGG)

(c) Rice codon optimized Cas9 was cloned along with maize ubiquitin1 (Ubi1) promoter and PINII as transcriptional stop signal. (d) Hygromycin-ZsYellow construct was selected as plant selectable/scorable marker with Ubi1 promoter and PINII as transcriptional stop signal. (e) All three cassettes were cloned into single binary vector backbone (Fig. 6b). 11. Vector construction designing protocol to edit one amino acid in rice MS26 gene by SDN2 (Fig. 7).

126 a.

Amit Das et al. Cytochrome P450 (Os03g07250.1)

Cas9-gRNA target

b. UBI Pro

Rice U6 Pro

GGATGGTGACGTACGTGCCCTACTCCATGGGGAGG

NLS1

Cas9

Target

NLS2

gRNA scaffold

PINII

Poly T

c. d.

Edited plants

Wild type

e. No. of variants screened

No. of variant detected

efficiency (%)

Monoallelic variant (%)

Bi-allelic variant (%)

34

19

55.9

8 (42.1)

11 (57.9)

Ms26

f.

NGS sequence analysis

Selfed: No seed Wild Type

ms26 edited plant

Fig. 8 Rice MS26 gene editing. Editing of rice MS26 gene (cytochrome P450) by SDN1 approach. (a) Rice MS26 locus with gRNA target (bold) and PAM sequence (underlined). (b) Cas9 and gRNA expression cassettes. (c) NGS analysis of target sequence of edited plants and wild type. (d) Indel frequency analysis based on nucleotide number of SDN1 edits. (e) SDN1 frequency analysis in regenerated plants. (f) Phenotypic study of ms26 edited plant as compared to wild type

(a) The targeted amino acid is glycine (Gly) which is to be edited to tryptophan (Trp) (Figs. 7 and 8). (b) Codon for Gly is GGG and the first base (G) is to be substituted by T resulting TGG that encodes for Trp. (c) The target base “G” is also the third base of PAM sequence (TGG), thereby conferring protection of the edited gene against gRNA following repair process inside the cell. (d) The repair template contains “T” in place of “G.” (e) Additional bases in PAM proximal may be altered using codon degeneracy to protect HDR product (not shown in graphic). (f) The single-stranded repair template can be synthesized with 50 nucleotides each to upstream and downstream of gRNA target as homology arms to the target locus.

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Table 1 Different methods, reagents, and explants used for plant transformation with CRISPR-Cas construct Transformation method Reagent

Explant

Agrobacterium

Binary plasmid DNA

Immature embryo, seed-derived callus

Particle gun

Plasmid DNA, short oligos, riboprotein complex consisting Immature embryo, of Cas9 protein-gRNA transcript seed-derived callus

Polyethylene glycol

Plasmid DNA, short oligos, riboprotein complex consisting Protoplast of Cas9 protein-gRNA transcript

Electroporation

Plasmid DNA, short oligos, riboprotein complex consisting Protoplast of Cas9 protein-gRNA transcript

(g) It can also be cloned as double-stranded DNA with 100–500 bp homology arms on each side or can be used as single-stranded oligo in transformation process. 3.3 Plant Transformation

Rice transformation by Cas9-gRNA constructs is primarily performed by Agrobacterium or particle gun method with suitable modifications (Table 1, Fig. 8a–f) [20, 42–45]. The general process is described below.

3.3.1 Isolation of Immature Embryos for Transformation

(a) Harvest panicles 12–15 days after pollination stage. They contain immature embryos at the right developmental stage and are good for transformation. (b) Remove the hull from immature seeds with forceps or by hands. Sterilize the immature seeds in a sterile 50 ml tube using sodium hypochlorite solution (with 4% active chlorine) for 5 min and wash 4–5 times with sterile distilled water. (c) Isolate immature embryos from the seeds with the help of forceps or by hands. Wash embryos in 1 ml of sterile distilled water for 3–4 times. Place embryos in resting media for 1–2 days, and then use as the starting material for transformation.

3.3.2 Preparation of Scutellum-Derived Callus

(a) Dehusk the rice seeds and select only healthy seeds (discard brown, black, and shrunken seeds), then soak de-hulled seeds in 50 ml of sterile water containing a drop of Tween 20, and keep in the shaker at 200 rpm for 5 min. Then discard the water and completely remove the foam by repeated washing. (b) Followed by sterilization with 75% ethanol for 2–3 min. (c) Sterilize the seeds in 50 ml of sodium hypochlorite solution (with 4% active chlorine) with a drop of Tween 20 for 15–20 min.

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(d) Rinse the seeds 4–5 times using sterile water. Each time use at least 100 ml sterile water and ensure that the foam is removed completely. (e) Decant water completely and blot dry the sterile seeds by placing them onto several layers of sterile filter paper. Transfer the seeds onto callus induction medium, placing 15–20 seeds on each plate (90 mm). (f) Culture the seeds under continuous light at 28–32  C for 12 days. 3.3.3 Transformation by Particle Gun Method

(a) Entry or binary vector plasmid DNA is coated onto gold particles using standard procedures [46]. They are bombarded onto tissue culture plate containing immature embryos/callus using Bio-Rad Helium gun (PDS1000) [20]. (b) Twenty four-hour post bombardment, explants were transferred to resting medium for few days (5–7 days). (c) After resting, transfer explant pieces on selection medium supplemented with appropriate concentration of selectable chemical agent like hygromycin (based on the marker used) [42, 43]. (d) After 2 weeks, individual explant pieces are again transferred to fresh selection medium. Within 6–8 weeks of bombardment, hygromycin-resistant clones emerge from selected calli pieces. (e) After this, proliferating highly embryogenic calli were transferred to regeneration medium and incubated at 28  C in light culture room for 4 weeks. (f) After 4 weeks, plantlets and roots are formed on the calli. These plantlets were moved to rooting medium to allow further growth. (g) Well-rooted plantlets are shifted to greenhouse, one plant per selected calli is taken as more often, and plants from one calli are clonal.

3.3.4 Transformation by Agrobacterium Method

Plant transformation through Agrobacterium method requires all the components, gRNA, Cas9, and marker cassettes. These are cloned in single binary vector which is mobilized into Agrobacterium strain. Immature embryos are co-cultivated using standard procedures [43, 44, 47]. The rest of the steps of transformation process are same as described under particle gun method.

3.3.5 Transformation Using Riboprotein Complex of Cas9 Protein-gRNA Transcript

Rice immature embryo or freshly prepared protoplast has been transformed with pre-assembled complex of Cas9 protein and in vitro synthesized gRNA transcript [20, 21]. This process is DNA-free for SDN1 strategy, but DNA repair template is required for SDN2 in addition to the riboprotein complex.

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The major steps are as follows: (a) Design oligo and synthesize according to guidance of gRNA synthesis kit (as per manufacturer’s instruction). (b) In vitro synthesis instruction).

of

gRNA

(follow

manufacturer’s

(c) Purification and yield confirmation. (d) In vitro assembly of gRNA transcript and Cas9 protein: l

l l

l

For each shot, mix Cas9 protein 10 pmol/1.5 μg (Cas9, 160 kDa) and gRNA 20 pmol/600 ng (~ 1:2 molar ratio; gRNA 100 nucleotides). Cas9 protein, 20 μM/400 pmol/20 μl; conc. 20 pmol/μl. Reaction mix, NEB buffer 3, RNase inhibitor (1–2 μl) with total volume 20 μl; incubate at RT for 15–30 min. Keep in ice till used for micro carrier preparation.

(e) Preparation of gold microcarrier: l l

l l

Per shot gold, 500 ng. A vial with 3 mg/50 μl gold washed with RNase-free water three times and finally resuspended with 70–80 μl RNasefree water. Add Cas9 and gRNA assembly mix. Add 2 μl water-soluble cationic lipid solution, TransIT™-2020 reagent (#MIR5404, Mirus Bio™, USA) and mix by short vortexing.

l

Wash with ethanol before putting onto macrocarrier.

l

Air-dry for 1–2 h.

(f) Bombardment with PDS1000/He gun: l

650/900 psi.

l

Keep immature embryos on osmoticum medium (2 days before bombardment).

l

Subculture and regeneration.

l

Transfer to subculture media from osmoticum and keep for 7–10 days at incubator (dark), transfer to regeneration media, and keep for 10 days, followed by rooting (10 days) and hardening (3 days) [43, 44].

(g) Screening and selection of variant: l

Next-generation sequencing (NGS) for single guide and PCR/qPCR for dual guides.

l

NGS for selecting lead variant.

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3.4 Molecular Analysis of Genome Edited Lines

Identification of desired edits is performed by various molecular biology and sequencing tools. Conventional polymerase chain reaction (PCR) or quantitative PCR (qPCR)-based approach can be used to detect SDN1 mutations generated by two/multiple guides. However, short indels or edits generated by single guide (SDN1) or repair template-mediated SDN2 edit require advanced sequencing processes like next-generation sequencing (NGS) of the target region. Sometimes, diagnostic restriction digestion can be performed to identify desired edits with unique restriction enzyme. Novel application of probe-based screening like Southern-bySequencing (SbS) can be performed to detect a clean plant edit without any vector backbone [48]. Below are the basic steps to screen T0 plants generated by Cas9-gRNA complex. (a) Transfer healthy, robust, and well-rooted plantlets (T0) from transformation lab to growth chamber or greenhouse. (b) Sample leaf tissues before transplanting for determining the occurrence of mutation either by NGS (single nucleotide mutation) or by PCR followed with NGS analysis to confirm the large fragment deletion [16, 49]. (c) Plants containing deletions (few bps to few 100 bps) as well as couple of lines which are negative for mutation are retained to be used as no deletion control for further advancement and phenotypic characterization. Careful selection of target sequence and gRNA design are crucial to avoid/minimize off target modifications, if any. Software based tools for prediction of off targets can be utilized to identify such loci and these genomic region(s) can be sequenced by NGS in the genome edited plant to detect any such occurrence.

3.5 Phenotyping of Genome Edited Line

Once the plant with desired edit is identified through molecular analysis (Fig. 8c), the T0 plant is characterized phenotypically for various parameters (e.g., overall plant health and vigor, height, number of tillers, panicles, flowering time, spikelet fertility, grain yield, etc.) and self-crossed to produce T1 seeds (Fig. 8f). Phenotyping in T0 stage may be an indicative of intended phenotypes depending on type of mutation (monoallelic or biallelic, Fig. 8d, e) and trait of interest or function of the target gene (Fig. 8f). T1 plants can be further selected on the basis of the presence of desired edit and absence of vector T-DNA. Selection for absence of any vector/introduced DNA is critical step in the process. These selected plants are free of any foreign DNA and harbor only intended edits. Additionally, any off-target screening can be performed either in T0 or T1 plants and can also be outcrossed with wild-type parent for few generations to eliminate/segregate any potential pleiotropic effect that may arise due to the process. Please note that the Cas9 protein and other vector backbone sequences can also be segregated by the outcrossing process. Once clean

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Table 2 List of agronomic traits for phenotypic characterization of genome edited lines Grain Drought Disease yield Lodging tolerance resistance Sterility

Target area Gross phenotyping (vigor, height, flowering time, tillers, grain yield)

√

√

√

√

√

Yield parameters (productive tillers, panicle length, √ spikelet fertility, total yield, test weight) Culm length, strength, cell count per unit area, lignin measure Drought and recovery profile, relative water content Lesion length after pathogen infection; % of infection

√

√ √ √

Pollen viability

√

Crossing to check male or female sterility/fertility

√

genome edited lines have been selected, these are used for phenotyping for agronomic traits; some common parameters (and those unique to trait of interest) are summarized in Table 2. This list is not exhaustive and depending on trait of interest and depth of analysis required, more features may be needed to be assessed. 3.6

Discussion

Application of genome editing technology by CRISPR-Cas for crop improvement requires diverse set of capabilities—from lab to field. It needs modern gene analysis software along with competency to identify guide RNA target in the target genome, as well as suitable facilities for molecular biology, tissue culture, and phenotyping. A team with multidisciplinary expertise may greatly facilitate setting up of an efficient high-throughput genome editing platform. Generation of a genome edited rice line typically requires 5–6 months depending on crop life cycle and availability of resources. The edited gene can result in complete loss-of-function or altered function which arises due to frameshift or in-frame indels. It can also lead to altered expression of the native gene if any regulatory sequence is edited without affecting protein coding sequence. Once a gene edit is generated using plasmid DNA, the Cas9-gRNA expression cassette together with plant selection marker can be eliminated from the edited genome in subsequent generations either by segregation, followed by selfing or outcrossing with wild-type parent. In case of riboprotein complex-mediated transformation method, the edited plant remains free of any foreign DNA even at the first generation (T0). Irrespective of the methods used, this feature of absence of introduced/foreign DNA in the

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final edited plants has made genome editing technology completely different from the transgenic approach (where the foreign DNA is integrated and is positively selected throughout all the generations in transgenic crop genome) and is similar to that of conventional plant breeding. CRISPR-Cas-based genome editing can be used either as a tool to explore naturally occurring allelic space in the target germplasm or to generate novel alleles. Conventional plant breeding can be limiting due to lack of availability of germplasm/ desired alleles in parental lines and the repeated backcross breeding required for elimination/reduction of the donor genome. Genome editing process can be used with diverse germplasms of a target crop irrespective of individual genetics, besides eliminating the scope of acquiring undesired trait due to linkage drag in a muchreduced time frame. CRISPR-Cas-assisted genome editing of a crop plant can be employed to generate superior and diverse agronomic features, for example, better grain yield, disease resistance, drought tolerance, altered maturity, impart quality traits, etc. In order to do efficient and efficacious edits, it is important to have an in-depth knowledge about the structure-function relationship of the candidate gene and its allelic space in target species or variety. Proper selection of the edited line is also another major factor, as the edit should not generate any pleotropic effect which potentially can affect additional agronomic traits. Overall, CRISPR-Cas-assisted crop genome editing is being widely explored to generate advanced crop plants with better agronomic features and has shown great promise to produce affordable food to feed the growing world population in forthcoming future. However, the adoption to this exciting and game-changing technology for crop improvement as well as human health is going to be directly proportional to the regulatory regime.

Acknowledgments The work was carried out at the DuPont Knowledge Centre, Corteva Agriscience™, Hyderabad, India. We’d like to thank the senior leadership of Corteva for their guidance and support. The authors would also like to thank Dharmendra Patil, Syam Sura, Geeta Pogula, Nilesh Sapkal, Girish Chandra, and Sunder Reddy for their diligent work. The support of the Applied Science and Technology (AST) group of Corteva for molecular analysis of the edited lines is duly acknowledged. The options expressed in this manuscript are of the authors and not that of the Corteva Agriscience™. References 1. Makarova KS, Grishin NV, Shabalina SA, Wolf YI, Koonin EV (2006) A putative RNA-

interference-based immune system in prokaryotes: computational analysis of the predicted

Genome Editing of Rice by CRISPR-as enzymatic machinery, functional analogies with eukaryotic RNAi, and hypothetical mechanisms of action. Biol Direct 1:7 2. Jansen R, Embden JD, Gaastra W, Schouls LM (2002) Identification of genes that are associated with DNA repeats in prokaryotes. Mol Microbiol 43:1565–1575 3. Barrangou R, Fremaux C, Deveau H, Richards M, Boyaval P, Moineau S, Romero DA, Horvath P (2007) CRISPR provides acquired resistance against viruses in prokaryotes. Science 315(5819):1709–1712 4. Jinek M, Chylinski K, Fonfara I, Haer M, Doudna J, Charpentier E (2012) A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337:816–821 5. Wyman C, Kanaar R (2006) DNA doublestrand break repair: all’s well that ends well. Annu Rev Genet 40:363–383 6. Gaj T, Gersbach CA, Barbas CF (2013) ZFN, TALEN, and CRISPR/Cas-based methods for genome engineering. Trends Biotechnol 31:397–405 7. Waterworth WM, Drury GE, Bray CM, West CE (2011) Repairing breaks in the plant genome: the importance of keeping it together. New Phytol 192:805–822 8. Podevin N, Davies HV, Hartung Nogue´ F, Casacuberta JM (2013) Site-directed nucleases: a paradigm shift in predictable, knowledge-based plant breeding. Trends Biotechnol 31:375–383 9. Shan Q, Wang Y, Li J, Zhang Y, Chen K, Liang Z, Zhang K, Liu J, Xi JJ, Qiu JL, Gao C (2013) Targeted genome modification of crop plants using a CRISPR-Cas system. Nat Biotechnol 31:686–688 10. Li JF, Norville JE, Aach J, McCormack M, Zhang D, Bush J, Church GM, Sheen J (2013) Multiplex and homologous recombination-mediated genome editing in Arabidopsis and Nicotiana benthamiana using guide RNA and Cas9. Nat Biotechnol 31:688–691 11. Feng Z, Zhang B, Ding W, Liu X, Yang DL, Wei P, Cao F, Zhu S, Zhang F, Mao Y, Zhu JK (2013) Efficient genome editing in plants using a CRISPR/Cas system. Cell Res 23:1229–1232 12. Mao Y, Zhang H, Xu N, Zhang B, Gao F, Zhu J-K (2013) Application of the CRISPR-Cas system for efficient genome engineering in plants. Mol Plant 6(6):2008–2011 13. Xie K, Yang Y (2013) RNA-guided genome editing in plants using a CRISPR-Cas system. Mol Plant 6:1975–1983

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genomic DNA without DNA cleavage. Nature 551(7681):464–471 39. Li C, Zong Y, Wang Y, Jin S, Zhang D, Song Q, Zhang R, Gao C (2018) Expanded base editing in rice and wheat using a Cas9adenosine deaminase fusion. Genome Biol 19:59 40. Eid A, Alshareef S, Mahfouz MM (2018) CRISPR base editors: genome editing without double-stranded breaks. Biochem J 475:1955–1964 41. Sambrook J, Fritsch EF, Maniatis T (1989) Molecular cloning, a laboratory manual, vol 1–3, 2nd edn. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY 42. Hiei Y, Ohta S, Komari T, Kumashiro T (1994) Efficient transformation of rice (Oryza sativa L.) mediated by Agrobacterium and sequence analysis of the boundaries of the T-DNA. Plant J 6:271–282 43. Mohanty A, Kathiria H, Ferjani A, Sakamoto A, Mohanty P, Murata N, Tyagi AK (2002) Transgenics of an elite indica rice variety Pusa Basmati 1 harbouring the codA gene are highly tolerant to salt stress. Theor Appl Genet 106:51–57 44. Mohanty A, Sarma NP, Tyagi AK (1999) Agrobacterium-mediated high frequency transformation of an elite indica rice variety Pusa Basmati 1 and transmission of the transgenes to R2 progeny. Plant Sci 147:127–137 45. Hiei Y, Komari T (2008) Agrobacteriummediated transformation of rice using immature embryos or calli induced from mature seed. Nat Protoc 3:824–834 46. Tomes DT, Ross MC, Songstad DD (1995) Direct DNA transfer into intact plant cells via microprojectile bombardment. In: Gamborg OL, Phillips GC (eds) Plant cell, tissue and organ culture. Springer lab manual. Springer, Berlin, Heidelberg, pp 197–213 47. Slamet-Loedin IH, Chadha-Mohanty P, Torrizo L (2014) Agrobacterium-mediated transformation: rice transformation. Methods Mol Biol 1099:261–271 48. Zastrow-Hayes GM, Lin H, Sigmund AL, Hoffman JL, Alarcon CM, Hayes KR, Richmond TA, Jeddeloh JA, May GD, Beatty MK (2015) Southern-by-sequencing: a robust screening approach for molecular characterization of genetically modified crops. Plant Genome 8:1–15 49. Brooks C, Nekrasov V, Lippman ZB, Van Eck J (2014) Efficient gene editing in tomato in the first generation using the clustered regularly interspaced short palindromic repeats/ CRISPR-Associated9 system. Plant Physiol 166:1292–1297

Chapter 9 Single Base Editing Using Cytidine Deaminase to Change Grain Size and Seed Coat Color in Rice My Vo Thi Tra, Xiaojia Yin, Ishita Bajal, Christian Paolo Balahadia, William Paul Quick, and Anindya Bandyopadhyay Abstract The fast-moving CRISPR technology has allowed plant scientists to manipulate plant genomes in a targeted manner. So far, most of the applications were focused on gene knocking out by creating indels. However, more precise genome editing tools are demanded to assist the introduction of functional single nucleotide polymorphisms (SNPs) in breeding programs. The CRISPR base editing tools were developed to meet this need. In this chapter, we present a cytidine deaminase base editing method for editing the point mutations that control the grain size and seed coat color in rice. Key words CRISPR, Base editing, Cytidine deaminase, Rice

1

Introduction Traditional plant breeding programs exploit genetic variation for desired crop characteristics. Recent years, the CRISPR/Cas9 (clustered regularly interspaced short repeats/CRISPR-associated protein 9) [1, 2] was proven to be an efficient genome editing tool for plant genomes [3, 4]. The Cas9 endonuclease is assisted by a guide RNA (gRNA) to bind the targeted DNA in a genome and to create a double-strand break (DSB), resulting insertions and deletions (indels) at the target locus through the nonhomologous end joining (NHEJ) gene repairing mechanism. CRISPR/Cas9 is a promising tool for crop improvement. Its application for targeted gene knocking out is so far an unprecedented success. However, more precise genome manipulating approaches are still in high

My Vo Thi Tra and Xiaojia Yin contributed equally Electronic Supplementary Material: The online version of this chapter (https://doi.org/10.1007/978-10716-1068-8_9) contains supplementary material, which is available to authorized users. Anindya Bandyopadhyay and Roger Thilmony (eds.), Rice Genome Engineering and Gene Editing: Methods and Protocols, Methods in Molecular Biology, vol. 2238, https://doi.org/10.1007/978-1-0716-1068-8_9, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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demand. Introducing desired alleles by conventional breeding programs is time and labor intensive. Precise genome manipulation protocols by error-free homology-directed repair (HDR) are still under optimization [5, 6]. Recently, a novel programmable approach called base editing was developed to meet this need [7– 9]. This approach irreversibly converts the targeted single base without needing any DSB and homologous repair template. Many cases of successful editing for crops were reported [10–13]. The base editors in this chapter contain several key components: (a) Inactivated Cas9 It is a catalytically dead Cas9 (dCas9) or nickase Cas9 (nCas9) containing mutations at the catalytic domain (dCas9, D10A and H840A; nCas9, D10A) that inactivate the nuclease activity. The ability of DNA binding by gRNA is remained without inducing any DNA DSB. (b) Cytidine deaminase It is the enzyme which catalyzes the conversion of cytosine to uracil. (c) XTEN linker The XTEN linker is a hydrophilic polypeptide used for the fusion of proteins or peptides of interest. The 16 residue XTEN gives a balance between cytidine deaminase and the inactivated Cas9 and an approximately five-nucleotide deamination window [14]. (d) Uracil DNA glycosylase inhibitor (UGI) When G:U mismatches present in cells, the uracil N-glycosylase will excise the uracil in the base excision repair (BER) mechanism. The UGI in a base editor will prevent the removal of uracil and therefore assist the conversion of cytidine to uridine. There are many reported functional SNPs in crops associating with important agricultural traits [15, 16]. Here we report the application of cytidine deaminase base editor editing the gain-offunction SNP in rice SMALL GRAIN 11 (OsSMG11) [17] and rice BROWN HULL 6 (OsBH6) [18]. The OsSMG11 is a novel allele of DWARF2 (D2), encoding a cytochrome P450 (CYP90D2) involved in the brassinosteroid biosynthesis pathway. The gene was identified from the ethyl methanesulfonate (EMS)-treated M2 populations of the japonica variety Kuanyejing (KYJ) [19]. The Ossmg1 mutation has a C to T missense mutation. The proline codon (74CCC) was substituted to leucine (74CTC), resulting in small grain, dense panicles, and increased secondary panicle branch number and grain number per panicle.

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Flavonoids as secondary metabolites have important physiological functions in dormancy and viability of seeds [20]. The brown hull 6 (bh6) is an EMS mutant that exhibits obvious brown pigment in the furrows of glumes after pollination and even darker pigmented in mature seeds. This phenotype is due to a single base substitution (G/A) at position 1013 of an F-box domain-containing protein (FBX310) that changed one amino acid at position 338 from glycine to aspartic acid (338GGC - > 338GAC).

2

Materials

2.1 Generation of the pCambia-CRISPR-BE Backbone Vector

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Plasmids: pCambia1300, pnCas9-PBE (from SnapGene, 98164), pZB-sgRNA-NAG, and pZB-sgRNA-NGG.

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Oligos: OsSMG11-F, OsSMG11-F, OsFBX310-F, OsFBX310R (Table 1).

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Enzymes: AarI, KpnI-HF, BamHI-HF, HindIII-HF, SpeI-HF, NheI-HF, T4 DNA ligase.

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GenUP™ Gel Extraction Kit.

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GenUP™ Plasmid Isolation kits.

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E. coli TOP10.

Table 1 List of oligos and their sequences

Primer

Sequence 50 –30

Junction 2-BE3-F Junction 2-BE3-R Outside-RB-F ZmUbi-R XY_73F_OsU3

GGGAGAACAAGATCAAGATGC GTCGTGCTCCACATCATCGA CTGTCGCGTAACTTAGGACTTGTG GAGGTTGGGGAAAGAGGGTG ATGTGCAGTCAGGGACCATAG

Screening of colony

FBX310-CCN-F FBX310-CCN-R OsSMG11-F OsSMG11-R

GGCAGACGGCGCCCGTCGCCGGCA AAACTGCCGGCGACGGGCGCCGTC GGCAGCCCCGAGGCGTTCGTCGAC CAAAGTCGACGAACGCCTCGGGGC

gRNA oligos

FBX-F FBX-R SMG11-F SMG11-R

GAGTGAAGCATGCAGACAGC ATGACGCGTCCCAACGCC GGTTATTTGGGTGGTGCTGT GGAGAAGAAGGAGGACGTAC

For heteroduplex in T7 assay and sequencing

rAPOBEC1-F rAPOBEC1-R Hyg-F Hyg-R

GGAAGGTTTCATCGGAGACC CTTCTTGTCCTTAAGTTCAGGC GATGTTGGCGACCTCGTATT GTGCTTGACATTGGGGAGTT

Transgene screening

Purpose of using

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2.2 Isolation of Rice Protoplasts

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MilliporeSigma SLHV033RB Millex® HV Sterile Syringe Filter with Durapore® PVDF Membrane, 0.45 μm.

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Sodium hypochlorite and Tween 20.

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Razor blades.

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40 μm Falcon® Cell Strainers.

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Chemicals (Sigma-Aldrich): Mannitol MES, CaCl2, NaCl, KCl, MgCl2, acetone, FDA.

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0.1% BSA (bovine serum albumin).

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Enzymes: Cellulase RS (Yakult), macroenzyme (Yakult).

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Stereomicroscope.

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Fluorescence microscope.

2.3 Transient Expression in Rice Protoplasts

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Chemicals (Sigma Aldrich): PEG4000, mannitol, CaCl2, KCl, MES.

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Isolated plasmid DNA.

2.4 Rice Transformation

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Immature embryos of indica rice cultivar IR64.

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Agrobacterium (LBA4404).

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YEB Agrobacterium Growth Medium and Bacto Agar.

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Sodium hypochlorite and Tween 20.

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Instruments: forceps, scalpel.

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Filter paper.

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3 M Micropore tape.

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Media: infection medium, co-cultivation medium, resting medium, selection medium, pre-regeneration medium, regeneration medium, Yoshida-conventional culture (YCS) solution as stated previously [4].

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SBS Taq DNA Polymerase PCR reagent.

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Q5 High-Fidelity DNA Polymerase.

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T7 Endonuclease I (NEB).

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GenUPTM Gel Extraction Kit.

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Digest pCambia-1300 with KpnI-HF and BamHI-HF and isolate the 8954 bp digested DNA fragment.

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Digest pnCas9-PBE with KpnI-HF and HindIII-HF and isolate the 1989 bp Ubi promoter fragment.

2.5 Screening and Verification

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Methods

3.1 Generation of the pCambia-CRISPR-BE Backbone Vector

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Digest pnCas9-PBE with HindIII and SpeI-HF to get 5964 bp APOBEC1-XTEN-nCas9-UGI fragment.

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Digest pZB-sgRNA-NAG and pZB-sgRNA-NGG scaffold with NheI-HF and BamHI-HF to get the 519 bp gRNA scaffold.

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3.2 Generation of Working Vector 3.2.1 pCambiaCRISPR-BE-SMG11 Cloning

3.2.2 pCambiaCRISPR-BE-Osfbx310 Cloning

Ligate the four DNA fragments with T4 DNA ligase at 16  C overnight or at 23  C for 1 h to get pCambia-CRISPR-BE-NAG backbone vector and pCambia-CRISPR-BE-NGG backbone vector.

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Transform the ligated product in E. coli TOP10. Inoculate a single colony that is PCR positive (Junction 2-BE3-F and Junction 2-BE3-R; Outside-RB-F and ZmUbi-R) in liquid medium for plasmid DNA isolation.

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The target mutation in OsSMG1 is C to T at proline codon 74. An NAG PAM is available at this locus that has the target nucleotide within the deamination window (see Notes 1 and 2)

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Dilute the oligos OsSMG11-F and OsSMG11-R to 10 mM (sequence in Table 1). Mix 5 μL of each oligo and allow it to be heated up to 95  C for 5 min on a heat block. Naturally cool the mixture to room temperature to form the annealed oligo.

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Digest pCambia-CRISPR-BE-NAG with AarI and isolate the 17,086 bp fragment AarI- pCambia-CRISPR-BE-NAG.

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Ligate the AarI-pCambia-CRISPR-BE-NAG and the annealed oligo to have pCambia-CRISPR-BE-SMG11 vector.

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Transform pCambia-CRISPR-BE-SMG11 to E. coli and select a PCR (XY_73F_OsU3 and OsSMG11-R)-positive colony for sequence verification.

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The target mutation in Osfbx310bh6 is glycine codon 338 to aspertic (338GGC to 338GAC). An NGG PAM is available at this locus that has the target nucleotide within the deamination window (Table 2).

Table 2 SNP location of Ossmg11 and Osfbx310bh6 Gene OsSMG11

Osfbx310bh6

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SNP and gRNA location

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3.3 Isolation of Rice Protoplasts and Transient Expression

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Dilute the oligos FBX310-CCN-F and FBX310-CCN-R to 10 mM (sequence in Table 1). Mix 5 μL of each oligo and allow it to be heated up to 95  C for 5 min on a heat block. Naturally cool the mixture to room temperature to form the annealed oligo.

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Digest pCambia-CRISPR-BE-NGG with AarI and isolate the 17,086 bp fragment AarI-pCambia-CRISPR-BE-NGG.

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Ligate the AarI-pCambia-CRISPR-BE-NGG and the annealed oligo to have pCambia-CRISPR-BE-Osfbx310 vector.

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Transform pCambia-CRISPR-BE-SMG11 to E. coli and select a PCR (XY_73F_OsU3 and FBX310-CCN-R)-positive colony for sequence verification.

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Dehull and sterilize indica rice IR64 seeds with 75% ethanol for 1 min. Sterilize the seeds further with 2.5% sodium hypochlorite containing a drop of Tween 20 for 30 min. Wash the seeds with sterile water for at least five times. Dry the sterilized seeds on filter paper and germinate them on 1/2 MS medium at 28  C for 10 days with a photoperiod 12 h light/12 h dark.

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Prepare 30 mL of enzyme solution (1.75% cellulase R10, 0.875% Macerozyme R10, 0.6 M mannitol, 10 mM MES at pH 5.7, water). This solution should be pre-warmed at 50  C with a stirring bar to dissolve the enzymes completely. Add 10 mM CaCl2 and 0.1% BSA and filter sterilize the solution through 45 μm filter.

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Cut the 10-day-old seedlings into approximately 0.5 mm strips using sterilized double edge razor blades. Transfer the strips immediately (see Note 3) to the enzyme solution and incubate for 5 h in the dark at 28  C incubator without shaking (see Note 4).

l

l

l

After the enzymatic incubation, filter the solution with 40 μm cell strainer (Falcon® Cell Strainers) into 50 mL Falcon tubes. Add equal volume of W5 solution (154 mM NaCl, 125 mM CaCl2, 5 mM KCl, and 2 mM MES at pH 5.7) twice in the remaining strips followed by 20 s of gentle hand swirling and filter the solution. Centrifuge the filtered solution at 50  g for 5 min with a bench swinging bucket centrifuge (see Note 5). Wash the pellet with W5 solution and resuspend in MMG solution (0.4 M mannitol, 15 mM MgCl2, and 4 mM MES at pH 5.7). Take less than 5% of the total protoplast solution to another tube and stain with FDA acetone solution (final concentration at 0.01% w/v). Checked the quality and viability of protoplasts with a hematocytometer under fluorescence microscope with UV filter. Dilute the protoplast solution to a concentration of 2  106 cells/mL.

Cytidine Deaminase Base Editor in Rice l

l

l

3.4 Rice Transformation

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Mix 10 μg of plasmid DNA with 200 μL of protoplast solution (2  106 cells/mL). Prepared PEG solution freshly before transformation (40% W/V, PEG 4000 in 0.2 M mannitol and 0.1 M CaCl2). Mix the PEG solution and the protoplast solution that contains plasmid DNA (see Note 6). Incubate at room temperature for 30 min in the dark. After incubation, add 440 μL W5 solution to wash away the PEG in the mixture. Protoplasts were pelleted by centrifuge at 50  g for 3 min. Gently suspend the transformed protoplasts in 1 mL of WI solution (0.5 M mannitol, 20 mM KCl and 4 mM MES at pH 5.7) and incubate at dark for 24 h.

l

YFP plasmid (yellow fluorescent protein) can be transformed as positive control. If the YFP transformed protoplasts show the fluorescence under the fluorescence microscope, the DNA of protoplasts transformed with CRISPR base editor constructs can be exacted for PCR and sequencing verification.

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Streak Agrobacterium LBA4404 that is transformed with the working vector on YEP plate with 50 mg/L kanamycin antibiotic the day before rice transformation and incubate at 28  C for 16–24 h.

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Select healthy panicles at 8–12 days from anthesis. Dehull and sterilize the fresh immature seeds with 70% ethanol. Then wash the seeds with 1% sodium hypochlorite and one drop of Tween 20 for 5 min. Repeat washing with sterile distilled water for at least five times to remove the sodium hypochlorite. Isolate immature embryos under stereomicroscope inside a sterile laminar hood.

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Pick up incubated Agrobacterium from the plate to a 1.5 mL tube and dilute to OD 0.3 with infection medium.

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Drop 5 μL of the Agrobacterium infection medium on top of each immature embryo, and incubate in the dark at 25  C for 7 days.

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After the incubation, cut off the elongated shoots and blot the transfected immature embryos on sterile filter paper to inhibit the overgrowing of bacterial. Place the immature embryo on resting medium for 5 days under continual illumination at 30  C.

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After 5 days resting, cut each embryo into four pieces and transfer them on selection medium with 30 mg/mL of hygromycin, and incubate for 10 days.

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Transfer the healthily developing calli to fresh selection medium and incubate for another 10 days.

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3.5 Screening and Verification of Success of Editing

4

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Transfer the healthily developing calli for the third time selection for 10 days.

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Transfer the resistant calli to pre-regeneration medium and incubate for another 10 days.

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Transfer proliferating calli to regeneration medium for 14 days.

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Transfer regenerated plantlets to the Styrofoam netted holes submerged with YCS solution.

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Allow the roots to develop in YCS solution for 2 weeks (change fresh solution every week). Transplant healthy plantlets to pots with soil.

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Isolate genomic DNA from T0 transgenic plants and perform PCR with two pairs for primers (rAPOBEC1-F and rAPOBEC1-R; Hyg-F and Hyg-R) to detect the transgene integration.

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Amplify the targeted genomic region using high-fidelity Q5 DNA polymerase (SMG11-F and SMG11-R for pCambiaCRISPR-BE-SMG11; FBX-F and FBX-R for pCambiaCRISPR-BE-Osfbx310 transformants). Perform this PCR with genomic DNA from both wild-type and the transgenic plants.

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Mix 1:1 of the PCR products from wild-type and the transgenic plants to form a heteroduplex. Digest the annealed heteroduplex with 0.5 U/μL of T7 Endonuclease I for 1–2 h and stop the reaction by adding 0.25 M EDTA.

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Run the digested electrophoresis.

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Select the T7-positive samples for sequencing verification at the target locus.

product

on

1.5–2.0%

agarose

gel

Notes 1. The target base to be edited needs to fall into the editing window. 2. The editing activity order (underlined is the expected base 0 0 0 0 0 0 0 0 change) is 5 TC3 > 5 CC3 > 5 AC3 > 5 GC3 . 3. It is important to transfer the seedling strips in to the solution as quickly as you can to avoid the plasma membrane disruption. 4. During the protoplast isolation, please make sure all the strips are submerged in the enzyme solution. 5. Set the centrifuge deceleration at 0 or “off” to allow the centrifuge stop naturally. This can reduce protoplast damages. 6. The mixing has to be gentle but quick. If any clump of green tissue is seen, the transformation is failed.

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Acknowledgments Authors acknowledge International Rice Research Institute for funding. References 1. Jinek M, Chylinski K, Fonfara I, Hauer M, Doudna J, Charpentier E (2012) A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337:816–821 2. Cong L, Ran FA, Cox D, Lin S, Barretto R, Habib N, Hsu PD, Wu X, Jiang W, Marraffini LA, Zhang F (2013) Multiplex genome engineering using CRISPR/Cas systems. Science 339:819–823 3. Jiang W, Zhou H, Bi H, Fromm M, Yang B, Weeks DP (2013) Demonstration of CRISPR/ Cas9/sgRNA-mediated targeted gene modification in Arabidopsis, tobacco, sorghum and rice. Nucleic Acids Res 41:1–12 4. Yin X, Biswal AK, Dionora J, Perdigon KM, Balahadia CP, Mazumdar S, Chater C, Lin HC, Coe RA, Kretzschmar T, Gray JE, Quick WP, Bandyopadhyay A (2017) CRISPR-Cas9 and CRISPR-Cpf1 mediated targeting of a stomatal developmental gene EPFL9 in rice. Plant Cell Rep 36:1–13 5. Puchta H (2005) The repair of double-strand breaks in plants: mechanisms and consequences for genome evolution. J Exp Bot 56:1–14 6. Miki D, Zhang W, Zeng W, Feng Z, Zhu JK (2018) CRISPR/Cas9-mediated gene targeting in Arabidopsis using sequential transformation. Nat Commun 9:1967 7. Komor AC, Kim YB, Packer MS, Zuris JA, Liu DR (2016) Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Nature 533:420–424 8. Komor AC, Badran AH (2017) Editing the genome without double-stranded DNA breaks. ACS Chem Biol 13:383–388 9. Gaudelli NM, Komor AC, Rees HA, Packer MS, Badran AH, Bryson DI, Liu DR (2017) Programmable base editing of A·T to G·C in genomic DNA without DNA cleavage. Nature 551:464–471 10. Zong Y, Wang Y, Li C, Zhang R, Chen K, Ran Y, Qiu J, Wang D, Gao C (2017) Precise base editing in rice, wheat and maize with a Cas9-cytidine deaminase fusion. Nat Biotechnol 35:438–440

11. Hua K, Tao X, Yuan F, Wang D, Zhu JK (2018) Precise a·T to G·C base editing in the rice genome. Mol Plant 11:627–630 12. Kim JS (2018) Precision genome engineering through adenine and cytosine base editing. Nat Plants 4:148–151 13. Li H, Qin R, Liu X, Liao S, Xu R, Yang J, Wei P (2019) CRISPR/Cas9-mediated adenine base editing in rice genome. Rice Sci 26:125–128 14. Schellenberger V, Wang CW, Geething NC, Spink BJ, Campbell A, To W, Scholle MD, Yin Y, Yao Y, Bogin O, Cleland JL, Silverman J, Stemmer WP (2009) A recombinant polypeptide extends the in vivo half-life of peptides and proteins in a tunable manner. Nat Biotechnol 27:1186–1190 15. Dwivedi SL, Scheben A, Edwards D, Spillane C, Ortiz R (2017) Assessing and exploiting functional diversity in germplasm pools to enhance abiotic stress adaptation and yield in cereals and food legumes. Front Plant Sci 8:1461 16. Huq A, Akter S, Nou S, Kim HT, Jung YJ, Kang KK (2016) Identification of functional SNPs in genes and their effects on plant phenotypes. J Plant Biotechnol 43:1–11 17. Duan P, Rao Y, Zeng D, Yang Y, Xu R, Zhang B, Dong G, Qian Q, Li Y (2014) SMALL GRAIN 1, which encodes a mitogenactivated protein kinase kinase 4, influences grain size in rice. Plant J 77:547–557 18. Xia X, Xiao-Bo Z, Yong-Feng S, Hui-Mei W, Bao-Hua F, Xiao-Hong L, Qi-Na L-XHS, Dan G, Yan H, Jian-Li W (2016) A point mutation in an F-box domain-containing protein is responsible for brown hull phenotype in rice. Rice Sci 23:1–8 19. Fang N, Xu R, Huang L, Zhang B, Duan P, Li N, Luo Y, Li Y (2016) Small grain 11 controls grain size, grain number and grain yield in rice. Rice 9:64 20. Lepiniec L, Debeaujon I, Routaboul JM, Baudry A, Pourcel L, Nesi N, Caboche M (2006) Genetics and biochemistry of seed flavonoids. Annu Rev Plant Biol 57:405–430

Chapter 10 Analysis of Off-Target Mutations in CRISPR-Edited Rice Plants Using Whole-Genome Sequencing Guanqing Liu, Yiping Qi, and Tao Zhang Abstract The CRISPR/Cas systems have become the most widely used tool for genome editing in plants and beyond. However, CRISPR/Cas systems may cause unexpected off-target mutations due to sgRNA recognizing highly homologous DNA sequence elsewhere in the genome. Whole-genome sequencing (WGS) can be used to identify on- and off-target mutation. Here, we describe a pipeline of analyzing WGS data using a series of open source software for analysis of off-target mutations in CRISPR-edited rice plants. In this pipeline, the adapter is trimmed using SKEWER. Then, the cleaned reads are mapped to reference genome by applying BWA. To avoid mapping bias, the GATK is used to realign reads near indels (insertions and deletions) and recalibrate base quality controls. Whole-genome single nucleotide variations (SNVs) and indels are detected by LoFreq*, Mutect2, VarScan2, and Pindel. Last, SNVs and indels are compared with in silico off-target sites using Cas-OFFinder. Key words CRISPR, Off-target, WGS, SKEWER, GATK, LoFreq*, MuTect2, VarScan2, Pindel, CasOFFinder, Cas9, Cas12a

1

Introduction Genome editing is a useful technology for functional genomics, precise medicine, and plant breeding. In recent years, sequencespecific nucleases (SSNs) for genome editing have been improved rapidly, from zinc-finger nucleases (ZFN) to TAL effector nucleases (TALEN) and then to CRISPR (clustered regularly interspaced short palindromic repeats) nucleases [1]. These SSNs can recognize specific DNA sequence to induce DNA double-strand breaks, which may result in mutations due to error-prone nonhomologous end joining (NHEJ) repair. However, all these SSNs may introduce off-target mutations in the genome. For example, if a single guide RNA (sgRNA) has a protospacer that is highly homologous to other sites in the genome, CRISPR/Cas systems may potential induce off-target mutations at such sites [2, 3].

Anindya Bandyopadhyay and Roger Thilmony (eds.), Rice Genome Engineering and Gene Editing: Methods and Protocols, Methods in Molecular Biology, vol. 2238, https://doi.org/10.1007/978-1-0716-1068-8_10, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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Several systems have been optimized for alleviating off-target effects such as high fidelity Cas9 proteins [4], FokI-dCas9 fusions [5], truncated sgRNAs [6], and ribonucleotide protein (RNP) delivery [7]. Three new Cas family proteins were also identified and applied as new genome editing tools, such as Cas12b, Cas13a, and Cas14 [8–10]. At present, Cas9 and Cas12a are two widely used CRISPR genome editing systems in plants. However, Cas9 may cause off-target mutations when sgRNAs recognize DNA sequences with minor (commonly 1–3) nucleotide mismatches, and off-target mutations can also be found when using a Cas12a system although Cas12a is generally more specific than Cas9 [11, 12]. Various software for predicting and identifying CRISPR offtarget sites in silico or in vivo have emerged in past few years, such as Digenome-seq [12], CIRCLE-seq [13], GUIDE-seq [5], and so on. But for CRISPR editing in plant, whole-genome sequencing (WGS) is an accurate and reliable method for discovering off-target events. At least three studies have used WGS for detecting offtarget mutations by Cas9 in plants such as Arabidopsis, tomato, and rice [6, 14, 15], but none of them put forward a sophisticated method for off-targeting analysis based on WGS data. Here we introduce a pipeline of analyzing WGS data for plant off-target screening using a set of open source software: SKEWER, BWA, GATK, LoFreq*, MuTect2, VarScan2, and Pindel. We then compare detected mutations with in silico off-target sites predicted by Cas-OFFinder. Our WGS based pipeline for plant off-target screening is a systematic and robust method, which has been successfully applied in rice with both Cas9 and Cas12a [16]. The chapter describes our pipeline to detect off-target mutations in Cas9 and Cas12a edited rice plants with high accuracy.

2

Materials In this pipeline, all the commands are run using Linux command line and are shown with a “$” prefix in the following description. The operation in this protocol uses a CentOS 7 Linux System with 16 CPUs and 64G RAM. We highly recommend a 64-bit version of Linux operating system with at least eight CPUs and 32G RAM and adequate disk space (see Note 1). To decide where and how to run the example dataset, we have to create a working directory called off-target_pipeline. Additionally, GATK, LoFreq*, MuTect2, VarScan2, and Cas-OFFinder are downloaded in the software folder, and WGS data are downloaded in the raw_data folder. Anaconda3, a convenient tool for installing other software, is installed in the user’s home directory and $HOME/anaconda3/ bin directory is added to the PATH environment variable. Here, $HOME means the user’s home directory, such as /home/
. $HOME/anaconda3/bin represents the path /home/< username>/anaconda3/bin in this example. All data, results, and tools except Anaconda3 are stored under the working directory. Before we start the analysis, we need to create a working directory under the user’s home directory using the following command: $ mkdir $HOME/off-target_pipeline

2.1 Anaconda3 Distribution

Anaconda is an open source distribution that is the easiest way to perform Python/R data science and machine learning on Linux. We use Anaconda3 to install several tools easily without source compiling. $ cd $HOME/off-target_pipeline $ mkdir software && cd software

Download the latest 64-bit Linux version of Anaconda3 Distribution from the Anaconda website: https://www.anaconda.com/ distribution/. (In this demonstration, we use the 2018.12 version of Anaconda3.) $ sh Anaconda3-[version]-Linux-x86_64.sh $ export PATH=$HOME/anaconda3/bin:$PATH $ conda $HOME/anaconda3/bin/activate

If you need more information about Anaconda install process, please follow Anaconda manual (https://docs.anaconda.com/ana conda/install/linux/). Several channels should be added; then part of software used in the pipeline can be installed using conda command [17]. Type the following commands to add channels to Anaconda. $ conda config --add channels defaults $ conda config --add channels bioconda $ conda config --add channels conda-forge

2.2 Whole-Genome Sequencing (WGS) Data

WGS data used for off-target analyzing should be downloaded from National Center for Biotechnology Information (NCBI, accession number PRJNA420933) or the Genome Sequence Archive in Beijing Institute of Genomics (BIG, accession number PRJCA000656) [16]. Sample WTA1, WTA2, WTA3, WTA4, WTB1, WTB2, WTB3, WTB4, WTC1, WTC2, WTC3, WTC4, C1, C2, J1, J2, R1, and R2 are retrieved. Among these samples, WT prefix samples are three generations (year 2015–2017) of wild-type (WT) rice plants; C1, C2, J1, and J2 are Cas9-edited plants, and R1 and R2 are Cas12a-edited plants. Each wild-type sample has four biological replicates and each geneedited sample has two biological replicates (see Note 2).

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In this demonstration, we detect the somatic mutations between each gene-edited sample and all WT samples and find out off-target mutations in gene-edited sample. $ cd $HOME/off-target_pipeline $ mkdir raw_data && cd raw_data

Here $HOME/off-target_pipeline means the path of the working directory off-target_pipeline. All data are downloaded in the gzipped FASTQ format from the BIG database. All pair-end data are named like CRR000000_f1.fq.gz and CRR000000_r2.fq.gz (if users download data from the NCBI or EBI, data are named like “SRR0000000”). 2.3 Reference Genome

BWA and GATK both need a reference genome to align the WGS reads. Besides, the reference genome should be indexed in advance. BWA software can directly take this job. $ cd $HOME/off-target_pipeline $ mkdir genome && cd genome

In this demonstration, we use rice (Oryza sativa) reference genome TIGR7 [18], which can be downloaded from the Rice Genome Annotation Project website (http://rice.plantbiology. msu.edu/). Genome file is downloaded with .con suffix in the genome folder. We need to download all genome files contained both nucleus and organelle DNA sequences (all.con, chrC.con and chrM.con) (see Note 3). Then all the sequences are combined into one FASTA format file. $ sed -i ’s/chrC|11562 osa1/ChrC/’ chrC.con $ sed -i ’s/chrM|11706 osa1/ChrM/’ chrM.con $ cat all.con chrC.con chrM.con > TIGR7.fa

To build an index, the BWA v0.7.17 [19] and SAMtools v1.9 [20] should be installed first. We use conda command from Anaconda3 to install these tools. $ conda install bwa=0.7.17 $ conda install samtools=1.9

Then, we can use BWA index and SAMtools dict and faidx to build reference genome index and BWA alignment index. $ bwa index TIGR7.fa $ samtools dict TIGR7.fa > TIGR7.dict $ samtools faidx TIGR7.fa

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In order to improve the accuracy of detection for SNPs and indels, a known SNP and Indel database file is required in this pipeline (see Note 4). Database file can be downloaded from Rice SNP-Seek Database (IRIC, http://snp-seek.irri.org/) [21]. $ cd $HOME/off-target_pipeline $ mkdir dbSNP && cd dbSNP

All files (*.bed, *.bim, *.fam) in 3 K RG 2.3mio biallelic indel Dataset and 3K RG 29mio biallelic SNPs Dataset should be downloaded. Then all files need to be unzipped (see Note 5). $ ls *.gz | xargs gunzip

PLINK [22], BCFtools [23] and TABIX [23] software are used for converting and combining these files into a bgzipped VCF format file. We use conda command from Anaconda3 to install these tools. $ conda install plink=1.90b4 $ conda install bcftools=1.9 $ conda install tabix=0.2.6

Then, PLINK software is used to convert BED format file into VCF file. $ plink --bfile Nipponbare_indel --recode vcf --out Nipponbare_indel $

plink

--bfile

NB_final_snp

--recode

vcf

--out

NB_final_snp

Converted VCF files need to change chromosome names and these files should be combined and sorted using BCFtools (see Note 6). $ cat mutation/VarScan2/pileup/Sample.pileup

Then type the following command to detect SNVs and indels by VarScan2. $ java -jar software/VarScan.v2.4.3.jar somatic mutation/ VarScan2/pileup/SampleB.pileup mutation/VarScan2/pileup/SampleA.pileup mutation/VarScan2/SampleA/SampleA_vs_SampleB -output-vcf

After each run, each sample will create a snv.vcf file and an indel. vcf file in the mutation/VarScan2/Sample directory. Output vcf files can be further classified by type and confidence using the following code. $ java -jar software/VarScan.v2.4.3.jar processSomatic mutation/VarScan2/SampleA/SampleA_vs_SampleB.snp.vcf $ java -jar software/VarScan.v2.4.3.jar processSomatic mutation/VarScan2/SampleA/SampleA_vs_SampleB.indel.vcf

After processing these vcf files, mutations are separated into six files based on somatic status and confidence. File types are listed as follows (left column, filename; right column, description): A_vs_B.snp.Germline. vcf

SNP with sites called germline mutations

A_vs_B.snp.Somatic.vcf SNP with sites called somatic mutations A_vs_B.snp.LOH.vcf

SNP with sites called loss of heterozygosity, or LOH

A_vs_B.indel. Germline.vcf

Indel with sites called germline mutations

A_vs_B.indel.Somatic. vcf

Indel with sites called somatic mutations

A_vs_B.indel.LOH.vcf

Indel with sites called loss of heterozygosity, or LOH

A_vs_B.snp.Germline. hc.vcf

SNP with sites called germline mutations (high confidence)

A_vs_B.snp.Somatic.hc. SNP with sites called somatic mutations (high vcf confidence) (continued)

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Indel with sites called germline mutations (high confidence)

A_vs_B.indel.Somatic. hc.vcf

Indel with sites called somatic mutations (high confidence)

A_vs_B.indel.LOH.hc. vcf

Indel with sites called loss of heterozygosity (high confidence)

Here A_vs_B.snp.Somatic.hc.vcf and unclassified indel file (SampleA_vs_SampleB.indel.vcf) will be used as VarScan2-detected SNVs and indels, respectively. 3.7

Run Pindel

$ cd $HOME/off-target_pipeline $ mkdir -p mutation/Pindel $ cd mutation/Pindel && mkdir WTA1 WTA2 WTB1 WTB2 WTC1 WTC2 C1 C2 J1 J2 R1 R2

Pindel need a config file containing the path of BAM file, insert size (the length of sequence between the paired-end adapters in paired-end sequence; in this demonstration we set it to 350), and sample name. Follow the command below to create each sample’s config file (separate by space). $ echo $HOME/off-target_pipeline/alignment/Sample_recal. bam 350 Sample > Sample/Sample_config.txt

Then we can use Pindel to call indels for each sample by typing the following commands. $ cd $HOME/off-target_pipeline $ pindel -f genome/TIGR7.fa -i mutation/Pindel/Sample/ Sample_config.txt -T 32 -o mutation/Pindel/Sample/Sample

After each run, Pindel will create nine files in the output directory mutation/Pindel/Sample. Files in the directory are listed as follows (left column, filename; right column, description): Sample_BP

Pindel called unassigned breakpoints

Sample_CloseEndMapped

Pindel called reads map only one end

Sample_D

Pindel called deletion

Sample_INT_final

Pindel called interchromosomal events

Sample_INV

Pindel called inversion

Sample_LI

Pindel called large insertion (continued)

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Pindel called reads pair

Sample_SI

Pindel called short insertion

Sample_TD

Pindel called tandem duplication

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Here Sample_D and Sample_SI files mean deletions and short insertions, which are used for the next step. We need to filter out very long deletions (>1000, other callers can’t detect) and convert Pindel output into VCF format using the following codes with pindel2vcf command. $ grep ChrID mutation/Pindel/Sample/Sample_D | awk ’{if ($3 mutation/Pindel/Sample/Sample_D.head $ grep ChrID mutation/Pindel/Sample/Sample_SI > mutation/ Pindel/Sample/Sample_SI.head $ pindel2vcf -R MSU_TIGR7 -r genome/TIGR7.fa -d 20190101 -p mutation/Pindel/Sample/Sample_D.head -v mutation/Pindel/ Sample/Sample_D.vcf $ pindel2vcf -R MSU_TIGR7 -r genome/TIGR7.fa -d 20190101 -p mutation/Pindel/Sample/Sample_SI.head -v mutation/Pindel/ Sample/Sample_SI.vcf $ cat mutation/Pindel/Sample/Sample_D.vcf mutation/ Pindel/Sample/Sample_SI.vcf | bedtools sort -i - -header | uniq > mutation/Pindel/Sample/Sample_indels.vcf

After merging and sorting vcf files by BEDTools, the final Sample_indels.vcf files will be used as Pindel-detected indels. 3.8 Run BEDTools to Filter Mutations

To generate high confidence SNVs and indels, replicates of each sample are overlapped. Finally, SNVs and indels called by different software are overlapped respectively. Use the following commands to filter detected mutations (software_name is the software folder name, and users should type “LoFreq,” “MuTect2,” and “VarScan2” to replace “software_name”). $ cd $HOME/off-target_pipeline $ cd mutation/software_name $ mkdir merged $ bedtools intersect -a Sample/Sample_vs_WTA1_snvs.vcf -b Sample/Sample_vs_WTA2_snvs.vcf -header | bedtools intersect -a - -b Sample/Sample_vs_WTA3_snvs.vcf -header | bedtools intersect -a - -b Sample/Sample_vs_WTA4_snvs.vcf -header | bedtools intersect -a - -b Sample/Sample_vs_WTB1_snvs.vcf -header | bedtools intersect -a - -b Sample/Sample_vs_WTB2_snvs.vcf -header

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Filter mutation on ChrSy, ChrUn, chloroplast, and mitochondria chromosome (sequencing results in these chromosomes are unreliable). $ cd $HOME/off-target_pipeline/mutation $ ls */merged/*.vcf | xargs sed -i "/ChrSy\|ChrUn\|ChrC\| ChrM/d"

Remove mutations shared in WTC samples by typing the following codes (here Sample is all gene-edited samples, not including WTC samples). $ cd $HOME/off-target_pipeline/mutation $ mkdir filter $ bedtools intersect -a merged/Sample_vs_WT_snvs.vcf -b merged/WTC1_vs_WT_snvs.vcf -header -v | bedtools intersect -a - -b merged/WTC2_vs_WT_snvs.vcf -header -v | bedtools intersect -a - -b merged/WTC3_vs_WT_snvs.vcf -header -v | bedtools intersect -a - -b merged/WTC4_vs_WT_snvs.vcf -header -v | uniq > filter/Sample_vs_WT_snvs.vcf $ bedtools intersect -a merged/Sample_vs_WT_indels.vcf -b merged/WTC1_vs_WT_indels.vcf -header -v | bedtools intersect -a - -b WTC2_vs_WT_indels.vcf -header -v | bedtools intersect -a - -b WTC3_vs_WT_indels.vcf -header -v | bedtools intersect -a - -b WTC4_vs_WT_indels.vcf -header -v | uniq > filter/ Sample_vs_WT_indels.vcf

Finally, merge each software results by samples using the following commands. $ cd $HOME/off-target_pipeline/mutation $ mkdir caller_merged $ bedtools intersect -a Lofreq/filter/Sample_vs_WT_snvs. vcf -b MuTect2/filter/Sample_vs_WT_snvs.vcf -header -v | bed-

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tools intersect -a - -b VarScan2/filter/Sample_vs_WT_snvs.vcf -header -v | uniq > caller_merged/Sample_vs_WT_snvs.vcf $ bedtools intersect -a MuTect2/filter/Sample_vs_WT_indels.vcf -b VarScan2/filter/Sample_vs_WT_indels.vcf -header -v | bedtools intersect -a - -b Pindel/Sample/Sample_indels.vcf -header -v | uniq > caller_merged/Sample_vs_WT_indels.vcf

The final Sample_vs_WT_snvs.vcf and Sample_vs_WT_indels. vcf files will be used for checking if off-target sites are existing in the samples. 3.9 Run CasOFFinder for In Silico Off-Target Detection

$ mkdir -p $HOME/off-target_pipeline/mutation/casoffinder $ cd $HOME/off-target_pipeline/mutation/cas-offinder $ cp $HOME/off-target_pipeline/genome/TIGR7.fa .

Use text editor (nano, vi, etc.) to create Cas-OFFinder config file. $ nano Type the following information in the text editor (path of genome file, PAM pattern and length, sgRNA sequence, and max mismatches) and save the file with name “Sample_seq.txt”. Sample C: $HOME/off-target_pipeline/mutation/cas-offinder NNNNNNNNNNNNNNNNNNNNNGG GCCGCATGGGCAGCAGCTGGNNN 10

Sample J-1 (see Note 10): $HOME/off-target_pipeline/mutation/cas-offinder NNNNNNNNNNNNNNNNNNNNNGG GCAGCTCTGACATGTGGGCCNNN 10

Sample J-2: $HOME/off-target_pipeline/mutation/cas-offinder NNNNNNNNNNNNNNNNNNNNNGG GTCCCGCGCTTCAAGGAGGTNNN 10

Sample R: $HOME/off-target_pipeline/mutation/cas-offinder TTTNNNNNNNNNNNNNNNNNNNNNNNN NNNNCAGAAAGAGAAGGAGGCACAGAT 11

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Type the following commands to search putative off-target sites in the rice reference genome. $ cd $HOME/off-target_pipeline $ software/cas-offinder mutation/cas-offinder/C_seq.txt C mutation/cas-offinder/C_out.txt $ software/cas-offinder mutation/cas-offinder/J-1_seq.txt C mutation/cas-offinder/J-1_out.txt $ software/cas-offinder mutation/cas-offinder/J-2_seq.txt C mutation/cas-offinder/J-2_out.txt $ software/cas-offinder mutation/cas-offinder/R_seq.txt C mutation/cas-offinder/R_out.txt

Output files in cas-offinder folder containing information of putative off-target sites such as position in genome, sequence, strand, and mismatch numbers compared to sgRNA sequence. Results

We used part of the data from the original paper [16]; thus this section only shows three gene-edited samples (Cas9-C, Cas9-J, and Cas12a-R) for on-target and off-target sites using Golden Helix GenomeBrowse® visualization tool v3.0.0 (see Note 11).

3.10.1 Count SNVs and Indels of Each Sample

Use the following command to count the number of mutations detected in each sample.

3.10

$ cd $HOME/off-target_pipeline/mutation/ caller_merged $ grep -v ’#’ Sample_vs_WT_snvs.vcf | wc -l $ grep -v ’#’ Sample_vs_WT_indels.vcf | wc -l

Then count the total number of mutations in each sample. True on-target site numbers should be excluded from the vcf file (e.g., if you have one on-target site in a sample, then count number is the number from the above command minus 1). Statistics are shown in Table 2. 3.10.2 Visualization and Validation of OnTarget Sites

Genome editing information are shown in Table 3 which contains alleles and positions. Here we use GenomeBrowse from Golden Helix to visualize and validate whether this information is correct through aligned WGS data (Fig. 2).

3.10.3 Find Off-Target Sites and Visualize the Sites

First, use the following commands to count the number of putative off-target sites based on mismatch numbers. $ cd $HOME/off-target_pipeline/mutation/casoffinder $ cut -f6 Sample_out.txt | sort | uniq -c | awk ’{print $2"\t"$1}’ | sort -k1n

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Table 2 Detected numbers of SNVs and indels of each sample Sample

Nucleases

SNVs

Indels

C1

Cas9

152

63

C2

Cas9

152

54

J1

Cas9

109

68

J2

Cas9

118

73

R1

Cpf1

174

74

R2

Cpf1

99

50

In Table 4, the left column means the mismatch number and the right column means the number of putative off-target sites. Here the first sgRNA of Cas9 Sample J has five positions that the genome sequence is identical with sgRNA sequence. All these five sites are considered as on-target site. Besides, for other samples, off-target sites are not detected when mismatch less than 3. If both two replicates are edited at the same site, and carry distinct alleles (mostly indels), then the site is more likely to be an off-target site. Check the shared mutation in replicates of each sample by typing the following codes (Sample1 and Sample2 represent two replicates). $ cd $HOME/off-target_pipeline/mutation/ caller_merged $ bedtools intersect -a Sample1_vs_WT_indels.vcf -b Sample2_vs_WT_indels.vcf | uniq $ bedtools intersect -a Sample1_vs_WT_snvs.vcf -b Sample2_vs_WT_snvs.vcf | uniq $ cd $HOME/off-target_pipeline/mutation/casoffinder $ awk ’{if($6>=1&&$640% GC content and preferably 50% to 70% GC content; (3) four or more consecutive “T” nucleotides should be avoided since they are terminator sequences for Pol III promoters; (4) conduct a secondary structure analysis of the candidate target-sgRNA sequences in order to prevent the formation of hairpin or stem structure which may decrease editing efficiency.

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Table 9 Primer sequences for amplification of the three sgRNAs fragments Primer name

Base sequence (50 ! 30 )

OsGS3-sgRNA1P1F

CACCGGTCTCAGTGTGGGCTTACTCTCTGCAGCATCGTTTTAGAGC TAGAAATA

General-P1R

CGCCAATATATCCTGTCAAA

General-P3F

TTTGACAGGATATATTGGCGAAGGGATCTTTAAACATACGAAC

OsGW2-sgRNA1P1R

CCTTTGTCTTTACACCACGACGCCACGGATCATCTGCAC AACT

OsGW2-sgRNA1P2F

TCGTGGTGTAAAGACAAAGGGTTTTAGAGCTAGAAATA

General-P2F

TTTGACAGGATATATTGGCGAGGATCCGCGGATCATG

OsGn1a-sgRNA1P2R

CGATGGTCTCCAAACCCC TGCAGGCGGCCGAGCGACACACAAGCGACAGCGC

2. Avoid BsaI site from the annealed sgRNA oligos. 3. Table 9 shows primers used for amplifying the fragments for the three sgRNAs targeting OsGS3, OsGW2, and OsGn1a.

Acknowledgments This work was supported by grants including the National Science Foundation of China (31771486), the Sichuan Youth Science and Technology Foundation (2017JQ0005), the National Transgenic Major Project (2018ZX08022001-003) and the Science Strength Promotion Program of UESTC to Y.Z., and the National Science Foundation Plant Genome Research Program (IOS-1758745) and USDA-NIFA Biotechnology Risk Assessment Research Program (2018-33522-28789) to Y.Q. References 1. Manuscript A (2007) NIH public access. 4 (11):911–916 2. Xu R, Yang Y, Qin R, Li H, Qiu C, Li L, Wei P, Yang J (2016) Rapid improvement of grain weight via highly efficient CRISPR/Cas9 mediated multiplex genome editing in rice. J Genet Genomics 43(8):529–532. https://doi. org/10.1016/j.jgg.2016.07.003 3. Zhou J, Xin X, He Y, Chen H, Li Q, Tang X, Zhong Z, Deng K, Zheng X, Akher SA, Cai G (2018) Multiplex QTL editing of grain-related genes improves yield in elite rice varieties. Plant

Cell Rep 38(10):1–11. https://doi.org/10. 1007/s00299-018-2340-3 4. Sunseri F (2017) Is genome editing techniques the new challenge for plant breeding? J Plant Genet Breed 1:e105 5. Rodrıguez-Leal D, Lemmon ZH, Man J, Bartlett ME, Lippman ZB (2017) Engineering quantitative trait variation for crop improvement by genome. Cell 171(2):470–480. https://doi.org/10.1016/j.cell.2017.08.030 6. Yan W, Chen D, Kaufmann K (2016) Efficient multiplex mutagenesis by RNA- guided Cas9

QTL Editing by CRISPR-Cas9 and its use in the characterization of regulatory elements in the AGAMOUS gene. Plant Methods 12(1):23. https://doi.org/10.1186/ s13007-016-0125-7 7. Mushtaq M, Bhat JA, Mir ZA, Sakina A, Ali S, Tyagi A, Salgotra RK, Dar AA, Bhat R (2018) CRISPR/Cas approach: a new way of looking at plant-abiotic interactions. J Plant Physiol 224-225:156–162. https://doi.org/10. 1016/j.jplph.2018.04.001 8. Ghimire B (2017) Use of Crispr/Cas9 for development of disease resistant cultivars in plant breeding. Int J Appl Sci Biotechnol 5 (4):403–409. https://doi.org/10.3126/ ijasbt.v5i4.18523 9. Gasparis S, Kała M, Przyborowski M, Łyz˙nik LA, Orczyk W, Nadolska-Orczyk A (2018) A simple and efficient CRISPR /Cas9 platform for induction of single and multiple, heritable mutations in barley (Hordeum vulgare L.). Plant Methods 14(1):111. https://doi.org/ 10.1186/s13007-018-0382-8 10. Kumar V, Jain M (2014) The CRISPR-Cas system for plant genome editing: advances and opportunities. J Exp Bot 66(1):47–57. https://doi.org/10.1093/jxb/eru429 11. Shen L, Hua Y, Fu Y, Li J, Lui Q, Jiao X, Xin G, Wang J, Wang X, Yan C, Wang K (2017) Rapid generation of genetic diversity by multiplex CRISPR/Cas9 genome editing in rice. Sci China Life Sci 60(5):506–515. https://doi. org/10.1007/s11427-017-9008-8 12. Qi W, Zhu T, Tian Z, Li C, Zhang W, Song R (2016) High-efficiency CRISPR/Cas9 multiplex gene editing using the glycine tRNAprocessing system-based strategy in maize. BMC Biotechnol 16(1):58. https://doi.org/ 10.1186/s12896-016-0289-2 13. Belhaj K, Chaparro-Garcia A, Kamoun S, Patron NJ, Nekrasov V (2015) Editing plant genomes with CRISPR/Cas9. Curr Opin Biotechnol 32:76–84. https://doi.org/10.1016/ j.copbio.2014.11.007 14. Hashimoto R, Ueta R, Abe C, Osakabe Y, Osakabe K (2018) Efficient multiplex genome editing induces precise, and self-ligated type mutations in tomato plants. Front Plant Sci 9:916. https://doi.org/10.3389/fpls.2018. 00916 15. Zhang Z, Mao Y, Ha S, Liu W, Botella JR, Zhu J (2016) A multiplex CRISPR/Cas9 platform

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for fast and efficient editing of multiple genes in Arabidopsis. Plant Cell Rep 35 (7):1519–1533. https://doi.org/10.1007/ s00299-015-1900-z 16. Feng Z, Zhang Z, Hua K, Gao X, Mao Y, Botella JR, Zhu J (2018) A highly efficient cell division-specific CRISPR/Cas9 system generates homozygous mutants for multiple genes in Arabidopsis. Int J Mol Sci 19 (12):3925. https://doi.org/10.3390/ ijms19123925 17. Xing H, Dong L, Wang Z, Zhang H, Han C, Lui B, Wang X, Chen Q (2014) A CRISPR/ Cas9 toolkit for multiplex genome editing in plants. BMC Plant Biol 14(1):327. https:// doi.org/10.1186/s12870-014-0327-y 18. Ma X, Liu Y (2016) CRISPR/ Cas9-based multiplex genome editing in monocot and dicot plants. Curr Protoc Mol Biol 115 (1):31–36. https://doi.org/10.1002/ cpmb.10 19. Wang M, Mao Y, Lu Y, Wang Z, Tao X, Zhu JK (2018) Multiplex gene editing in rice with simplified CRISPR-Cpf1 and CRISPR-Cas9 systems. J Integr Plant Biol 60(8):626–631. https://doi.org/10.1111/jipb.1263 20. Lowder LG, Zhang D, Baltes NJ, Paul JW, Tang X, Zheng X, Voytas DF, Hsieh TF, Zhang Y, Qi Y (2015) A CRISPR/Cas9 toolbox for multiplexed plant genome editing and transcriptional regulation. Plant Physiol 169 (2):971–985. https://doi.org/10.1104/pp. 15.00636 21. Tang X, Zheng X, Qi Y, Zhang D, Cheng Y, Tang A, Voytas DF (2016) A single transcript CRISPR-Cas9 system for efficient genome editing in plants. Mol Plant 9(7):1088–1091. https://doi.org/10.1016/j.molp.2016.05. 001 22. Xie K, Minkenberg B, Yang Y (2015) Boosting CRISPR/Cas9 multiplex editing capability with the endogenous tRNA-processing system. Proc Natl Acad Sci 112(11):3570–3575. https://doi.org/10.1073/pnas. 142029411223 23. Zheng X, Yang S, Zhang D, Zhong Z, Tang X, Deng K, Zhou J, Qi Y, Zhang Y (2016) Effective screen of CRISPR/Cas9-induced mutants in rice by single-strand conformation polymorphism. Plant Cell Rep 35(7):1545–1554. https://doi.org/10.1007/s00299-016-1967-1

Chapter 14 Rice Haploid Inducer Development by Genome Editing Juntao Liu, Dawei Liang, Li Yao, Ya Zhang, Chunxia Liu, Yubo Liu, Yanli Wang, Hongju Zhou, Timothy Kelliher, Xingping Zhang, and Anindya Bandyopadhyay Abstract The current method to induce haploids in rice is anther culture, which is time-consuming and labor intensive and only works for some varieties. Here we describe a seed-based haploid induction system created by CRISPR/Cas9 technology. By editing OsMATL, we generate rice haploid inducer lines with a 2–5% haploid induction rate in different germplasms. Key words CRISPR/Cas9, Genome editing, Haploid inducer, Rice, OsMATL, Pollination, Crossing

1

Introduction Haploid induction (HI) is the first step of application in the doubled haploid (DH) technology. For many crops there is no reliable HI system. To date, the only method to induce haploids in rice (Oryza sativa) is through anther culture, and this method is unsuccessful for many rice varieties [1]. Maize is the only crop that breeders utilize seed-based intraspecific crosses to produce haploids. All maize inducer lines are derived from Stock6, which sets ~3% maternal haploid seed with normally fertilized endosperm when crossed as a male donor [2]. The key mutation was found to be a 4 bp insertion causing a frameshift in the C-terminal domain of Matrilineal (MATL) [3], also called NOT LIKE DAD (NLD) [4] and Phospholipase A1 (PLA1) [5]. MATL is conserved in the cereals, but natural haploid inducer lines have not been identified outside of maize. The rice ortholog has a similar expression pattern to ZmMATL [6]. Here we use clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) 9 technology [7, 8] to create a series of OsMATL frameshift mutants in rice. The created mutants have ~6% haploid induction in the selfing population and a 2–5%

Anindya Bandyopadhyay and Roger Thilmony (eds.), Rice Genome Engineering and Gene Editing: Methods and Protocols, Methods in Molecular Biology, vol. 2238, https://doi.org/10.1007/978-1-0716-1068-8_14, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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haploid induction rate when crossing with different germplasms [9]. This work demonstrated the functional conservation of MATL and created rice haploid inducer lines, which represents a major breakthrough for rice breeding.

2

Materials

2.1

Plant Materials

The rice inbred line IR58025B was used for the Agrobacteriummediated transformation experiments [10]. Other lines could also be considered with optimization.

2.2

Media

Chemicals used in this study were purchased from Sigma-Aldrich (St. Louis, MO, USA). All the media were prepared using ultrapure distilled deionized water with pH adjusted to 5.8 and stored at 4
C unless otherwise indicated. LB medium: 10 g/L tryptone, 10 g/L NaCl, 5 g/L yeast extract, pH 7.0. Callus induction and pre-culture medium (NB): N6 majors, MS iron salts, B5 minors, B5 vitamins, 500 mg/L proline, 500 mg/L glutamine, 300 mg/L casein enzymatic hydrolysate, 30 g/L sucrose, 2 mg/L 2,4-D, 3 g/L phytagel. Bacteria culture medium (YEP): 5 g/L yeast extract, 10 g/L peptone, 5 g/L NaCl, 15 g/L bacto-agar, 100 mg/L spectinomycin, pH 7.2. Suspension medium: N6 majors, B5 minors, MS iron, B5 vitamin, 500 mg/L proline, 500 mg/L casein enzymatic hydrolysate, 2 mg/L 2,4-D, 20 g/L sucrose, 10 g/L glucose, 100 μmol/L acetosyringone, pH 5.2. Co-culture medium: Suspension medium solidified with 4 g/L phytagel, pH 5.2. Recovery medium (NBREC): NB supplemented with 250 mg/L carbenicillin. Selection medium (NBPMI): NBREC supplemented with 15 g/L mannose and 5 g/L maltose. Regeneration medium (NBIK): N6 majors, MS iron salts, B5 minors, B5 vitamins, 600 mg/L proline, 500 mg/L glutamine, 800 mg/L casein enzymatic hydrolysate, 30 g/L sucrose, 30 g/L sorbitol, 500 mg/L MES, 2.5 mg/L CuSO4, 2 mg/ L BA, 0.2 mg/L NAA, 2 mg/L IAA, 250 mg/L carbenicillin, 2 g/L phytagel. Rooting medium: 1/2 MB 1/2 MS basal salts (2.165 g/L), B5 vitamins, 1.0 g/L casein enzymatic hydrolysate, 20 g/L sucrose, 0.2 mg/L NAA, 125 mg/L carbenicillin, 3.5 g/L phytagel.

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2.3

KITs

223

MagneSil Paramagnetic Particles (Promega, Cat no. FF3761). KOD-PLUS-Neo (TOYOBO, Code No. KOD-401). OMEGA Gel Extraction Kit (D2500-02). QIAprep Spin Miniprep Kit (QIAGEN, 27106). pEASY vector (pEASY-Blunt Zero Cloning Kit, Transgen). Trans1-T1 Phage Resistant Chemically Competent Cell (Transgen, M810315). Applied Biosystems® TaqMan® (Applied Biosystems). ABsolute QPCR Mix, ROX (Thermo Scientific™).

2.4

Enzymes

All the enzymes below were purchased from New England Biolabs (NEB, UK): EcoRI (R0101). HindIII (R0104). AvrII (R0174). NcoI (R0193).

3

Methods

3.1 Confirm Genomic Sequence of OsMATL Gene in Rice Line IR58025B

1. Export sequence from reference genome of 93-11. Use Vector NTI (Life Technology) or any other software available to design primers to amplify 300–500 bp of genomic fragments around OsMATL (Os3g27610) exon 1 and exon 4. Primers used in this study are as below: Exon1-F: GCGTTCCTGCAAATCACAGTGACTA. Exon1-R: GATCGAAGAGAGGAGATCGAATTCG. Exon4-F: TAAGTTCCTGGTGCTGTCCGTGG. Exon4-R: TACAGTTACTAACGCTTGCACGCCA. 2. Extract genomic DNA of IR58025B using MagneSil Paramagnetic Particles (Promega, Cat no. FF3761). (a) Sample ~6 mm fresh leaf disks in a sealed 96-deep-well plate (Geno/Grinder®) in the presence of 300 μl of lysis buffer A and one grinding bead. (b) Process in the Geno/Grinder® following 1000 rpm, 3 min. Centrifuge 96-deep-well plates at 1700  g for 10 min to spin down cell debris. (c) Transfer 125 μl of each sample to the appropriate well of a new 96-well round bottom plate. Add 60 μl/well of buffer B mixture, and pipet to mix well.

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(d) Incubate at room temperature for 5 min, mix once by pipetting. Use fresh tips to avoid cross-contamination. (e) Place the plate onto the MagnaBot® 96 Magnetic Separation Device for 1 min. (f) Discard the liquid by pipetting/aspiration. Remove the plate from the MagnaBot® 96 Magnetic Separation Device, add 100 μl of nuclease-free water, and dissolve the DNA. 3. Carry out the following PCR reaction to amplify the target locus from genomic DNA. (a) 50 μl PCR system (see Note 1): 18.5 μl ddH2O, 5 μl buffer, 5 μl dNTPs, 3 μl MgSO4, 2.5 μl DMSO, 10 μM primers 2.5 μl each, 10 μl DNA templates, 1 μl KOD plus. (b) The PCR program is 95
C 5 min for denaturation, followed by 35 cycles of 94
C 20 s, 60
C 20 s, and 68
C 30 s and then 68
C 5 min for final extension and stored at 4
C until analyzed. 4. Run 5 μl of PCR product on 1.5% agarose gel to confirm the right size and send the rest to a commercial company (Life Technologies) for Sanger sequencing. 3.2 Design/Select gRNAs to Target OsMATL

1. Design gRNA within the PCR-confirmed genomic regions. For single target frameshift editing, the gRNA selection is not very critical. Any online gRNA design tool, such as RGEN (http://www.rgenome.net/cas-designer/), should work well. Basically, a 20 nt sequence 50 of NGG is selected. The GC content (NGG not included) is preferred to be 40–60%. No more than four continuous Ts were included. An in silico offtarget check should be conducted, such as RGEN Offinder (http://www.rgenome.net/cas-offinder/). The gRNA with high potential off-targets (7) indicating superior RNA integrity. The modifications described in this chapter were initially reported by Gautam et al. [11], and our observations reinforced that this modified LCM-based technique is suitable for RNA extraction from single cell type and analysis of their gene expression pattern [10, 11]. The schematic representation of the entire workflow is represented in Fig. 1.

Tissue processing

Cell Type Specific RNA Isolation Using LCM

Harvesting of tissue & fixation

< Day 1

Dehydration

< Day 2

Paraplast infiltration

277

< Day 3-5

Twice in a day

Paraplast embedding

< Day 6

Storage or

Sectioning and slide preparation

LCM & downstream applications

1d

LCM of cells/tissue 1d

RNA isolation and amplification 1-2d

RNA quality estimation Gene expression analysis

RT-PCR

Microarray/ RNA-Seq

Fig. 1 Schematic outline of the LCM-based method of RNA isolation. The method is divided into two parts: tissue processing and LCM and its downstream applications. The flowchart highlights the possible time involved in each step. “d” denotes day. This flowchart is reproduced from our previous publication [11]

2 2.1

Materials Reagents

1. Tissue sample: mature rice leaves 2. DEPC (Sigma-Aldrich, Cat. No. D5758) 3. Acetone (Fisher Scientific, Cat. No. A18-4) 4. Chloroform (Ranbaxy, Cat. No.C0200) 5. 100% isopropanol (Fisher Scientific, Cat. No.43566) 6. Agarose (Lonza, Cat. No.50004 L) 7. RNase out spray (GE Biosciences, Cat. No.786-71) 8. Paraplast (Sigma-Aldrich, Cat. No P3558) 9. 100% ethanol (Merck, Cat. No.1009830511) 10. TRI Reagent (Sigma-Aldrich, Cat. No. T9424) 11. Xylene (Fisher Scientific, Cat. No. X5-4) 12. RNase-free water (Sigma-Aldrich, Cat. No W4502) 13. Histoclear (Sigma-Aldrich, Cat. No H2779) 14. Mineral oil (Amresco, Cat. No. J217)

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15. DNase I (Thermo Fisher Scientific) 16. 3B DNA polymerase (Black Biotech, Cat. No. 3B009) 17. RiboAmp HS Plus RNA amplification kit (Arcturus, Applied Biosystems, Cat. No KIT0525) 18. SuperScript III reverse transcriptase (RT) enzyme (Invitrogen, Cat. No.18080-051) 2.2

Equipments

1. RM2265 rotary microtome (Leica Microsystems) 2. PALM microbeam laser capture microdissection (LCM) system (Carl Zeiss, http://microscopy.zeiss.com/microscopy/en_de/ home.html) 3. Agilent RNA 6000 nanochips (Agilent 5067-1511) 4. High-temperature oven (Scientific Systems, India) 5. Slide warmer (Medite OTS400) 6. Tissue floating water bath (Medite TFB55) 7. Peel-A-Way No. E6032)

embedding

mould

(Sigma-Aldrich,

Cat.

8. Agilent 2100 Bioanalyzer (http://www.genomics.agilent.com) 9. Metal hot plate (Scientific Systems, India) 10. Painting brush 11. Forceps 12. Disposable steel knife/blade (Leica Microsystems, Cat. No.140358838925) 13. Steel needles 14. Slide rack (Tarsons) 15. Glass coverslips (Himedia, Cat. No. CG115) 16. Plastic microcentrifuge tubes (1.5 mL) 17. Plastic microcentrifuge tubes (0.5 mL) 18. Nitrile gloves 19. Polypropylene conical tubes (50 mL) 20. Nanodrop 1000 (Thermo Fisher Scientific) 21. Aluminum foil 22. RNase-free charged glass slides (HistoBond+, Marienfeld Cat. No.0810411) 23. Thermal cycler (Applied Biosystems)

Cell Type Specific RNA Isolation Using LCM

3

279

Methods

3.1 Tissue Processing and Fixation

1. Cut up the desired tissue (rice leaves in this case) with an RNase-free scalpel in desired shape, and place in ice-cold acetone fixative kept in RNase-free vials [7, 9, 12]. 2. Vacuum infiltrate the tissue samples in ice-cold acetone at 4  C under 350 mm of Hg pressure for at least 15 min (for the enhanced invasion of the fixative) or until the tissue samples sink entirely to the bottom. Exposure to vacuum might be variable depending upon the tissue type (see Note 2). 3. Discard the fixative and replace with fresh ice-cold acetone, and place the sample vial at 4  C for overnight. 4. Dehydrate the tissue samples by sequential immersion in 3:1, 1:1, and 1:3 acetone:xylene grade at room temperature, 1 h at each step. Transfer the samples in 100% xylene, and incubate with mild agitation for another hour. 5. Add a few Paraplast chips to the sample immersed in 100% xylene, and keep at RT for overnight with agitation, and then transfer the vials at 57  C in the oven to melt down the Paraplast. Keep discarding the existing Paraplast and adding fresh molten Paraplast twice a day for the following 3 days (see Note 3).

3.2 Paraplast Embedding

1. After carrying out the aforementioned Paraplast replacements at 57  C, embed the leaf tissue in Peel-A-Way plastic disposable moulds or steel moulds or embedding rings. 2. Arrange the moulds on a hot plate at 57  C, dispense the tissue with molten Paraplast within, and set up the leaf samples in the preferred alignment with RNase-free forceps. 3. Allow the Paraplast to harden by shifting the moulds from the hot plate to RT, and keep at 4  C prior to further use. The moulds can be stored for an extended period at 4  C.

3.3 Tissue Sectioning

1. Trim the wax block containing the tissue into a required shape, and attach it in a preferred alignment on the plastic embedding rings. 2. Set the embedding rings on the holding clamp of the rotary microtome, and cut out thin sections of 8–10 μm width. 3. Place the tissue sections to HistoBond+ charged slides, and immerse slides into RNase-free water heated to 50–55  C for 3–5 min to flatten the sections, transfer slides to a hot plate at 42  C for 30 min to dry them up, and preserve at 4  C prior to LCM (see Note 4).

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Fig. 2 LCM of mesophyll and bundle sheath cells from mature leaves of O. sativa. (a) Bundle sheath cells before and (b) after LCM, (c) mesophyll cells before and (d) after LCM. The red outline indicates the selected region for LCM 3.4

LCM

1. Remove the wax from sections by immersing the slides for 3 min in Histoclear solution, and then dry the slides at RT. 2. Observe the slides primarily under a stereomicroscope to locate the tissue of interest and immediately transfer to an inverted microscope attached with LCM apparatus, find bundle sheath cells and/or mesophyll cells, and delineate them on-screen utilizing the PALM microbeam tool for dissection (Fig. 2). 3. Collect the microdissected tissue employing laser catapult in 0.5 mL RNase-free microfuge tube cap containing a drop of mineral oil, and preserve at
80  C for a brief period (see Note 5).

3.5

RNA Isolation

1. Centrifuge the microfuge tubes having LCM-derived tissues for 1 min at 1844  g, add 150 μL of TRI Reagent, and centrifuge the resultant mix for 2 min at 1844  g. 2. Add 100 μL of chloroform into the microfuge tube, vortex it for 5 s, incubate for 15 min at room temperature and centrifuge resultant mix for 30 min at 12,662  g.

Cell Type Specific RNA Isolation Using LCM

281

Fig. 3 (a) and (b) Bioanalyzer-based analysis of LCM-derived RNA for quality check (RIN Value), (c) LCM-based RNA isolation and expression analysis of OsGAPDH gene using the cDNA made from the RNA derived from bundle sheath cells (BS) and mesophyll cells (MC), (d) expression of OsPck1 in BS cells (positive control), absence of expression of OsPck1 in MC (negative control), expression of OsMe1 in BS (positive control), expression of OsMe1 in MC (positive control)

3. Replace the upper aqueous phase into a separate 1.5 mL microfuge tube, add equivalent proportion of isopropanol, incubate for 1 h at
20  C, and centrifuge at 12,662  g for 1 h. 4. Drain the supernatant without disturbing the pellet, add 100 μL of 70% ethanol, and centrifuge for 15 min at 4150  g to wash the pellet. 5. Dissolve the pellet in 10 μL of nuclease-free water, following air-drying. 6. Check the RNA integrity (RIN) and concentration of the RNA samples using Bioanalyzer nanochip and Nanodrop 1000, respectively (Fig. 3a, b). 7. If required, carry out RNA amplification twice using the RiboAmp HS Plus kit, following the user manual instruction [12, 13]. 8. Perform RNA precipitation (as described above, steps 3–5). 3.6

RT-PCR

by

adding

isopropanol

1. Treat about 1–2 μg of amplified RNA with recombinant DNase I, incubate for 10 min at 65  C to inactivate DNase I, and proceed for the first strand cDNA synthesis using SuperScript III RT [14–16]. 2. Use 2 μL of diluted (1:5) cDNA for setting a 20 μL PCR reaction using housekeeping gene primers for GLYCERALDEHYDE 3- PHOSPHATE D EHYDROGENASE (OsGAPDH) (Fig. 3c). The thermal cycling profile is as follows: 94  C for 50 :1; 94  C for 1500 , 60  C for 4000 , 72  C for 10 :40; 72  C for 100 and holding at 4  C.

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3. Expression of PHOSPHOENOLPYRUVATE C ARBOXYKI NASE (OsPck1) and NADP-MALIC ENZYME (OsMe1) is checked using the cDNA prepared from the RNA of bundle sheath cells and mesophyll cells. OsPck1 is known to express in bundle sheath cells and vascular cells, whereas OsMe1 expresses in the mesophyll cells, bundle sheath cells, and vascular cells [17]. This PCR reaction was carried out to check the specificity of the isolated RNA (Fig. 3d). The thermal cycling profile is as follows: 94  C for 50 :1; 94  C for 1500 , 60  C for 4000 , 72  C for 10 :40; 72  C for 100 and holding at 4  C. 4. Run the amplification product on 0.8–1% agarose gel.

4

Notes 1. All the steps including tissue collection, fixation, dehydration, wax embedding and sectioning, LCM, RNA isolation, and further downstream investigations are ought to be carried out in an RNase-free routine to avoid RNA degradation. 2. Slowly release the pressure after each turn of vacuum infiltration, and repeat the process until the tissue descends to the bottom of the vial. 3. Wax replacement should be performed carefully without damaging the tissue, and the temperature of the oven must be maintained at 57  C (not exceeding 60  C) to melt down the Paraplast. 4. Flattening of tissue sections on slides must be performed with caution and the temperature of the RNase free water should be less than 55  C (~ 50  C–54  C; depending on the nature of the tissue). 5. During the collection of laser catapulted microdissected tissue, the microfuge tube cap should be observed cautiously to ensure that the tissue gets collected.

Acknowledgments V.G. and S.C. thank the Council of Scientific and Industrial Research (CSIR), India, and the National Institute of Plant Genome Research (NIPGR), New Delhi, India, for funding and internal grants. VG also acknowledges the Department of Biotechnology (DBT), India, for fellowship. A.K.S. thanks NIPGR and DBT (Project Grant No.BT/PR12766/BPA/118/63/2015), New Delhi, India, for fellowship and grants. The authors declare no conflict of interests.

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References 1. Iyer-Pascuzzi AS, Benfey PN (2010) Fluorescence-activated cell sorting in plant developmental biology. Methods Mol Biol 655:313–319. https://doi.org/10.1007/ 978-1-60761-765-5_21 2. Herzenberg LA, Sweet RG (1976) Fluorescence-activated cell sorting. Sci Am 234(3):108–117 3. Birnbaum K, Jung JW, Wang JY, Lambert GM, Hirst JA, Galbraith DW, Benfey PN (2005) Cell type-specific expression profiling in plants via cell sorting of protoplasts from fluorescent reporter lines. Nat Methods 2(8):615–619. https://doi.org/10.1038/nmeth0805-615 4. Nawy T, Lee JY, Colinas J, Wang JY, Thongrod SC, Malamy JE, Birnbaum K, Benfey PN (2005) Transcriptional profile of the Arabidopsis root quiescent center. Plant Cell 17 (7):1908–1925. https://doi.org/10.1105/ tpc.105.031724 5. Emmert-Buck MR, Bonner RF, Smith PD, Chuaqui RF, Zhuang Z, Goldstein SR, Weiss RA, Liotta LA (1996) Laser capture microdissection. Science 274(5289):998–1001 6. Domazet B, Maclennan GT, Lopez-Beltran A, Montironi R, Cheng L (2008) Laser capture microdissection in the genomic and proteomic era: targeting the genetic basis of cancer. Int J Clin Exp Pathol 1(6):475–488 7. Kerk NM, Ceserani T, Tausta SL, Sussex IM, Nelson TM (2003) Laser capture microdissection of cells from plant tissues. Plant Physiol 132(1):27–35. https://doi.org/10.1104/pp. 102.018127 8. Ohtsu K, Smith MB, Emrich SJ, Borsuk LA, Zhou R, Chen T, Zhang X, Timmermans MC, Beck J, Buckner B, Janick-Buckner D, Nettleton D, Scanlon MJ, Schnable PS (2007) Global gene expression analysis of the shoot apical meristem of maize (Zea mays L.). Plant J 52(3):391–404. https://doi.org/10. 1111/j.1365-313X.2007.03244.x 9. Brooks L 3rd, Strable J, Zhang X, Ohtsu K, Zhou R, Sarkar A, Hargreaves S, Elshire RJ, Eudy D, Pawlowska T, Ware D, JanickBuckner D, Buckner B, Timmermans MC, Schnable PS, Nettleton D, Scanlon MJ (2009) Microdissection of shoot meristem functional domains. PLoS Genet 5(5):

e1000476. https://doi.org/10.1371/journal. pgen.1000476 10. Gautam V, Sarkar AK (2015) Laser assisted microdissection, an efficient technique to understand tissue specific gene expression patterns and functional genomics in plants. Mol Biotechnol 57(4):299–308. https://doi.org/ 10.1007/s12033-014-9824-3 11. Gautam V, Singh A, Singh S, Sarkar AK (2016) An efficient LCM-based method for tissue specific expression analysis of genes and miRNAs. Sci Rep 6:21577. https://doi.org/10.1038/ srep21577 12. Scanlon MJ, Ohtsu K, Timmermans MC, Schnable PS (2009) Laser microdissectionmediated isolation and in vitro transcriptional amplification of plant RNA. Curr Protoc Mol Biol Chapter 25:Unit 25A.23. https://doi. org/10.1002/0471142727.mb25a03s87 13. Ohtsu K, Schnable PS (2007) T7-based RNA amplification for genotyping from maize shoot apical meristem. CSH Protoc 2007:pdb prot4785 14. Verma S, Gautam V, Sarkar AK (2019) Improved laser capture microdissection (LCM)-based method for isolation of RNA, including miRNA and expression analysis in woody apple bud meristem. Planta 249 (6):2015–2020. https://doi.org/10.1007/ s00425-019-03127-0 15. Gautam V, Singh A, Singh S, Verma S, Sarkar AK (2019) Improved method of RNA isolation from laser capture microdissection (LCM)derived plant tissues. Methods Mol Biol 1933:89–98. https://doi.org/10.1007/9781-4939-9045-0_5 16. Nakazono M, Qiu F, Borsuk LA, Schnable PS (2003) Laser-capture microdissection, a tool for the global analysis of gene expression in specific plant cell types: identification of genes expressed differentially in epidermal cells or vascular tissues of maize. Plant Cell 15 (3):583–596 17. Nomura M, Higuchi T, Ishida Y, Ohta S, Komari T, Imaizumi N, Miyao-Tokutomi M, Matsuoka M, Tajima S (2005) Differential expression pattern of C4 bundle sheath expression genes in rice, a C3 plant. Plant Cell Physiol 46(5):754–761

Chapter 19 Immunolocalization Analysis of C4 Proteins in the Leaf Tissue of Rice Hsiang-Chun Lin, Joanne Jerenice An˜onuevo, William Paul Quick, and Anindya Bandyopadhyay Abstract Immunolocalization analysis is a principal tool to study protein expression and subcellular distribution in plant cells or tissues. In this chapter, we present the method of the preparation of lightly fixed fresh rice leaf tissue for immunolocalization analysis and detection of the protein of interest using fluorescent probes by fluorescent microscopy. This method especially does not need the process of embedding plant materials that saves time and prevents alterations of cellular compounds and structure during sample preparation. Using this method, the C4 rice project compared the expressions of the proteins of interest among C4 model plants, wild-type rice, and transgenic or mutant plants and successfully selected the transgenic plants with the correct location of each protein to create a C4 rice prototype. Key words C4 rice project, Immunolocalization, C4 proteins, OAA, PEPC, PCK, PPDK, ACP5, GFP, Confocal microscopy, TEM

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Introduction Rice is a staple food for more than three billion people in the world. To overcome the challenges such as rapid climate change and increase in population growth, high-yielding rice prototypes are immediately required in the near future. Improving photosynthetic rate has been reported as one of the most promising ways to increase rice yield [1]. Compared to C4 plants, C3 plants, such as rice and wheat, have a lower photosynthetic rate due to energy wasting in inefficient Rubisco activity and photorespiration. C4 plants have two-cell-type photosynthesis to concentrate CO2 surrounding Rubisco and boot photosynthesis rate twice higher than C3 plants. C4 rice project aims to transfer rice plants from C3 photosynthesis to C4 photosynthesis; therefore, rice can increase 50% of photosynthetic rate, double water use efficiency, improve nitrogen use efficiency, and double radiance use efficiency [2].

Anindya Bandyopadhyay and Roger Thilmony (eds.), Rice Genome Engineering and Gene Editing: Methods and Protocols, Methods in Molecular Biology, vol. 2238, https://doi.org/10.1007/978-1-0716-1068-8_19, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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To create a two-cell type of C4 photosynthesis in rice, C4 enzymes have to express in specific cell types. For example, phosphoenolpyruvate carboxylase (PEPC) in maize is specifically located in mesophyll cells where bicarbonate (HCO3ˉ) is first fixed to PEP by PEPC and initial C4 product, oxaloacetate (OAA), is generated. If C4 enzymes expressed in wrong cell types, the CO2 concentration mechanism will be broken down and photosynthesis will be reduced. To achieve the accuracy of enzyme expression, several mesophyll and bundle sheath cell-specific promoters have been identified and tested in rice [3, 4]. Maize PEPC promoter can drive gene expression in mesophyll cells, and on the other hand, Zoysia japonica phosphoenolpyruvate carboxykinase (PCK) promoter can be used for expressing genes in bundle sheath cells in rice. To verify whether C4 enzymes express in the correct cell types in transgenic rice plants, we performed immunolocalization analysis [5]. This allows the identification of protein locations in subcellular levels using specific antibodies for C4 enzymes. In the case of the unavailability of a specific antibody for the protein of interest, epitope tagging, such as AcV5, provides a fast and easy solution [6]. The recombinant protein with the epitope tag is detected with an antibody that is specific to the tag. To label the location of protein-antibody interaction, the direct method uses a singleprimary antibody, which recognizes and binds to the target protein and is directly conjugated with an enzyme, such as peroxidase using a chemical reaction to produce a color change, or a fluorescent probe, such as GFP or YFP [7]. Alternatively, the indirect method uses two antibodies, the primary antibody that specifically binds to the target protein and the secondary antibody that is conjugated with an enzyme or a fluorescent probe and specifically binds to the primary antibody. The labeled protein is visualized using highresolution light microscopy (LM), such as a confocal microscope or fluorescent microscope. LM, in combination with transmission electron microscopy (TEM) and immunolocalization analysis, provides the details of subcellular structure and localization of the proteins of interest in plant cells and tissues [8]. Together with biochemical and physiological techniques, it helps scientists to understand the function of proteins in plants [9, 10]. Here, we describe the method for the preparation of lightly fixed fresh rice leaf tissue for immunolocalization analysis and the indirect labeling method to target the protein of interest with a fluorescent probe for visualization with a fluorescent microscope. These methods enable us to save time and prevent degradations of cell compounds during the long process of embedding the plant tissues.

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Materials Tissue Fixation

1. Sample: young fully expanded seventh leaves of Oryza sativa spp. Indica rice cultivar IR64. 2. Fixative solution: 4% paraformaldehyde and 0.2% glutaraldehyde in 25 mM sodium phosphate buffer, pH 7.2 (see Note 1). 3. Tween 20. 4. 25 mM sodium phosphate buffer, pH 7.2 (see Note 2). 5. Razor blades. 6. Glass vials, 2 dram volume. 7. Transfer pipette, 1 mL. 8. Toothpicks. 9. A desiccator attached to a pump air compressor (see Note 3).

2.2

Hybridization

1. TBST buffer, pH 7.4: 20 mM Tris (Trizma base), 154 mM NaCl, and 0.1% Tween 20 (see Note 4). 2. Blocking solution: 3% low-fat milk powder in TBST buffer, pH 7.4. 3. 0.05% calcofluor white stain (see Note 5). 4. Primary antibody: specific to the protein of interest; diluted in blocking solution (see Note 6). 5. Secondary antibody: specific to the primary antibody and carry an appropriate fluorescent probe, diluted in blocking solution (see Note 7). 6. 96-well plates, 360 μL well volume. 7. Oven at 37  C.

2.3

Slide Preparation

1. 50% glycerol. 2. Glass microscope slides, pre-cleaned, 25  75  1 mm. 3. Glass coverslips, 22  22 mm. 4. Dark microscope glass slide storage box.

2.4 Viewing and Imaging

1. Fluorescence microscope with recommended filters for fluorescent probe labeling the protein of interest, chlorophyll autofluorescence, and calcofluor white stain (see Note 8). 2. Image processing software.

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Methods Rice Sampling

1. Remove the midrib of the leaf, and use a razor blade to cut the middle part of the leaf into 10 mm  3 mm pieces. 2. Transfer the pieces of tissue into the vial containing 7 mL of the fixative solution. 3. Use a transfer pipette to add five drops of Tween 20 into the vial, and invert the vial to mix the solution. 4. Place the vial uncapped in a desiccator attached to a piston pump air compressor, and allow tissue pieces to sink for 1–3 h, releasing vacuum pressure every 10 min and shaking the vials to remove the bubbles. 5. Remove the pieces that did not sink using a toothpick, and decant the fixative solution from the vial using a micropipette (see Note 9). 6. Refill the vial with a 7 mL fixative solution, and incubate at room temperature (24  C) for 3 h. 7. Decant fixative solution from the vial. 8. Wash the pieces by adding 7 mL of 25 mM phosphate buffer in the vial and incubating at room temperature for 15 min. Repeat this step four times. 9. Add 1 mL of 25 mM phosphate buffer in the vial. Store at 4  C (see Note 10), and process hybridization as described in Subheading 3.2.

3.2

Hybridization

1. Prepare a 96-well plate, and add 20 μL of 25 mM phosphate buffer in each well. 2. Cut fixed tissues into 0.1–0.2 mm thin sections (see Note 11) by hand using a razor blade, and gently place sections using a toothpick into the wells containing phosphate buffer to prevent drying. Limit to five sections per well. 3. Carefully remove phosphate buffer from the wells using a finetip transfer pipette, and replace it with 100 μL of blocking solution (see Note 12). Incubate for 2 h at room temperature. 4. Remove blocking solution using a fine-tip transfer pipette. Add 20 μL of primary antibody diluted in blocking solution, and incubate overnight at 4 C. 5. Remove the primary antibody using a fine-tip transfer pipette (see Note 13). 6. Wash the excess primary antibody from the sections by dispensing 20 μL of blocking solution to each well and then carefully removing the solution after 10 min using a new fine-tip transfer pipette. Repeat this step six times.

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7. Prepare the secondary antibody in a 1.5 mL Eppendorf covered in foil to avoid exposure to light and keep on ice. 8. Add 20 μL of the secondary antibody into each well. Cover the whole plate with foil to avoid exposure to light (see Note 14), and incubate for 2 h in a dark oven at 37  C. 9. Carefully remove secondary antibody from the wells using a new fine-tip transfer pipette. Minimize exposure to light by covering the well with foil throughout the process. 10. Wash the excess secondary antibody from the sections by dispensing 20 μL of blocking solution to each well and incubating for 10 min at room temperature. Carefully remove the blocking solution using a new fine-tip transfer pipette. Repeat this step six times, making sure that the sections are not exposed or only minimally exposed to light by covering the whole plate with foil. 11. Add 20 μL of 0.05% calcofluor white stain into each well, and incubate for 5 min at room temperature. 12. Remove calcofluor white stain using a fine-tip transfer pipette. 13. Wash the excess stain from the sections by dispensing 200 μL of autoclaved nanopure water into each well. Carefully remove the water. Repeat this step twice. 14. Add enough nanopure water to prevent the sections from drying out. 3.3

Slide Preparation

1. Label the clean glass slide accordingly with the sample name, date, and primary antibody, along with the concentration of the antibody used. 2. Add 50 μL of 50% glycerol to the center of the glass slide. Use a toothpick to get the sections from one well, and place these on the glycerol. 3. Carefully separate the sections, aligning them horizontally along the glass slide. Keep the sections within the perimeter of the coverslip (22 mm  22 mm). 4. Gently place a clean coverslip on the glass slide. Ensure that all of the sections are under the coverslip and are still horizontally aligned. Keep it inside the dark storage box in a 4  C refrigerator.

3.4 Viewing and Imaging

1. Set up the fluorescence microscope (such as Olympus BX61), and start the imaging software (such as CellSens). 2. View the bright-field images (Fig. 1a). 3. View the fluorescent images under a GFP filter for the protein of interest, which is labeled with Alexa Fluor 488 (Fig. 1b).

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Fig. 1 Example of immunolocalization of the H-subunit of glycine decarboxylase (GDCH) protein in the leaf of Oryza sativa spp. Indica rice cultivar IR64 generated by Lin et al. [9]. (a) Leaf cross section (bright-field images). (b) Expression of GDCH protein (GFP image). Anti-GDCH rabbit polyclonal primary antibody diluted 1:100 plus Alexa Fluor 488 goat anti-rabbit IgG as secondary antibody diluted 1:200 was used to probe for GDCH (shown in green color). (c) Chlorophyll is seen as a red autofluorescence (RFP image). (d) Image merged GFP, RFP, and BFP images. The cell wall was visualized by co-staining with calcofluor white and is shown in blue (BFP image). Magnification: 200. Scale bar: 20 μm

4. View the fluorescent images under an RFP filter for chloroplast, which has chlorophyll autofluorescence (Fig. 1c). 5. View the fluorescent images under a BFP filter for cell walls, which are stained with calcofluor white stain (Fig. 1d).

4

Notes 1. 125 mL 16% paraformaldehyde (0.1684 g/L paraformaldehyde powder in nanopure water, stirred at 60  C, NaOH pellet added until the solution becomes clear), 4 mL 25% glutaraldehyde, 125 mL 0.1 M sodium phosphate buffer, pH 7.2 (28 mL solution A: 0.278 g/L sodium phosphate monobasic in nanopure water; 72 mL solution B: 0.537 g/L sodium phosphate dibasic in nanopure water, adjust to pH 7.2), adjust to 500 mL with nanopure water.

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2. Dilute 25 mL 0.1 M sodium phosphate buffer by adding 75 mL nanopure water, adjust pH to 7.2. 3. You can also attach the desiccator to a speed vacuum concentrator. 4. 2.42 g/L Tris, 8.99 g/L NaCl, 10 mL 10% Tween 20, dissolved in 1.0 L nanopure water, pH adjusted to 7.4 with HCl. 5. 15 mL 1 g/L calcofluor white stain, 15 mL nanopure water. 6. The concentrations of primary antibody for immunolocalization analysis are usually high (1:20 to 1:200) that leads to adequate cell penetration. 7. It is important to ensure that the secondary antibody is compatible with the primary antibody and the ranges of absorption and emission wavelengths match to the filters in the microscope. A large number of Alexa Fluor secondary antibodies with different dyes or against different species are commercially available. 8. The specifics of how to choose a fluorescent probe or a suitable filter are described in Zhu et al. [11]. GFP filter is suitable for detecting Alexa Fluor 488 (excitation: 495 nm; emission: 519 nm). BFP filter is used for detecting cell walls that are stained with calcofluor white (excitation: 350 nm; emission: 440 nm), and RFP filter is used for viewing chloroplasts, which have chlorophyll autofluorescence (excitation: 488 nm; emission: 685, 740 nm). 9. Only use the pieces of tissue that sink to the bottom of the vial. 10. The pieces of the tissue sample can be stored in 25 mM phosphate buffer up to 6 months at 4  C. 11. Thin sections (0.1–0.2 mm) allow antibodies and stains to penetrate the cells. 12. Add and transfer solution slowly using the transfer pipette to prevent air bubbles and thin section damages happening. 13. The primary antibody solutions after use can be stored at 20  C and reused. However, a fresh antibody solution is recommended. 14. The addition of the fluorophore makes the sections light sensitive; therefore, from here onward, sections must be kept in the dark. This can be achieved by wrapping the plate with aluminum foil.

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References 1. von Caemmerer S, Quick WP, Furbank RT (2012) The development of C4 rice: current progress and future challenges. Science 336:1671–1672 2. Hibberd JM, Sheehy JE, Langdale JA (2008) Using C4 photosynthesis to increase the yield of rice—rationale and feasibility. Curr Opin Plant Biol 11:228–231 3. Matsuoka M, Kyozuka J, Shimamoto K, Kanomurakami Y (1994) The promoters of two carboxylases in a C4 plant (maize) direct cellspecific, light-regulated expression in a C3 plant (rice). Plant J 6:311–319 4. Nomura M, Higuchi T, Ishida Y, Ohta S, Komari T, Imaizumi N, Miyao-Tokutomi M, Matsuoka M, Tajima S (2005) Differential expression pattern of C4 bundle sheath expression genes in rice, a C3 plant. Plant Cell Physiol 46:754–761 5. Kajala K, Covshoff S, Karki S, Woodfield H, Tolley BJ, Dionora MJA, Mogul RT, Mabilangan AE, Danila FR, Hibberd JM, Quick WP (2011) Strategies for engineering a two-celled C4 photosynthetic pathway into rice. J Exp Bot 62:3001–3010 6. Lawrence SD, Novak NG, Slack JM (2003) Epitope tagging: a monoclonal antibody specific for recombinant fusion proteins in plants. BioTechniques 35:488–492 7. Hanson MR, Ko¨hler RH (2001) GFP imaging: methodology and application to investigate

cellular compartmentation in plants. J Exp Bot 52:529–539 8. Khoshravesh R, Lundsgaard-Nielsen V, Sultmanis S, Sage TL (2017) Light microscopy, transmission electron microscopy, and immunohistochemistry protocols for studying photorespiration. In: Fernie AR, Bauwe H, Weber APM (eds) Photorespiration: methods and protocols. Springer, New York, pp 243–270 9. Lin HC, Karki S, Coe RA, Bagha S, Khoshravesh R, Balahadia CP, Ver Sagun J, Tapia R, Israel WK, Montecillo F, de Luna A, Danila FR, Lazaro A, Realubit CM, Acoba MG, Sage TL, von Caemmerer S, Furbank RT, Cousins AB, Hibberd JM, Quick WP, Covshoff S (2016) Rice (Oryza sativa L. cv. IR64) plants with a knockdown in GDCH can survive in ambient air but exhibit a photorespiratory deficient phenotype. Plant Cell Physiol 57:919–932 10. Walker RP, Chen Z-H, Johnson KE, Famiani F, Tecsi L, Leegood RC (2001) Using immunohistochemistry to study plant metabolism: the examples of its use in the localization of amino acids in plant tissues, and of phosphoenolpyruvate carboxykinase and its possible role in pH regulation. J Exp Bot 52:565–576 11. Zhu H, Fan J, Du J, Peng X (2016) Fluorescent probes for sensing and imaging within specific cellular organelles. Acc Chem Res 49:2115–2126

Chapter 20 Selection of Suitable Reference Genes for qRT-PCR Gene Expression Studies in Rice Meng Wang and Navreet K. Bhullar Abstract With a widely established use of quantitative real-time PCR (qRT-PCR) for gene expression analysis, reliable and stable expression of reference genes is often discussed. Suitable reference genes should show less variation of expression across the target samples and allow for error minimization by normalization of qRT-PCR data. Therefore, selection of reliable reference genes is essential for accurate results and to support the conclusions drawn on expression levels of genes under study. In this chapter, we describe the workflow for selection and evaluation of reference genes in rice, including identification of candidate genes by using Genevestigator® and evaluation of expression stability using various algorithms. The ranking of the genes guides qRT-PCR performance and data analysis. This protocol used rice as an example but is not limited to rice, and could be applied to other species as well. Key words Rice, qRT-PCR, Reference genes, Genevestigator®, ΔCt approach, BestKeeper, NormFinder, geNorm

1

Introduction Quantitative real-time PCR (qRT-PCR) has become one of the most popular methods for gene expression quantification. It provides a robust means of detecting the mRNA levels due to its accuracy, high sensitivity, and repeatability [1]. However, several factors such as RNA purity, RNA integrity, reverse-transcription efficiency, and primer efficiency could affect the accuracy of qRT-PCR. Normalization achieved by using reference genes as internal controls is often required for qRT-PCR performance and data analysis. The reference genes are processed in parallel with the target genes through all experiment steps to avoid variations caused by sample preparation and PCR amplification. Ideally, the expression of reference genes should be stable across various tissues, development stages, and experiment conditions. Therefore, it is crucial to evaluate the performance of reference genes according to the set of samples [2–4] and the experimental conditions/treatments.

Anindya Bandyopadhyay and Roger Thilmony (eds.), Rice Genome Engineering and Gene Editing: Methods and Protocols, Methods in Molecular Biology, vol. 2238, https://doi.org/10.1007/978-1-0716-1068-8_20, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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The housekeeping genes such as ACTIN (ACT), ELONGATION FACTOR-1α (eEF-1α), β-TUBULIN (β-TUB), GLYCERALDEHYDE-3-PHOSPHATE DEHYDROGENASE (GAPDH), 18S rRNA are often assumed to express stably and are frequently used as reference genes for qRT-PCRs. However, studies demonstrated that transcript levels of these genes may fluctuate with changing physiological and experimental conditions [5, 6]. Today, with the genomic information advancements and availability of advanced transcriptome profiling techniques such as RNA sequencing, identifying novel and superior reference genes has become relatively more convenient [7, 8]. Being one of the most widely consumed staple food crops and a monocot model plant, the genome of rice is completely sequenced and well characterized. Further, numerous transcriptome profiling studies have been carried out in rice and these large datasets enable researchers to easily identify putative reference genes. In this chapter, we will introduce the workflow of selecting and evaluating the internal control genes for a specific set of samples (Fig. 1). The protocol described here was used to select reference genes suitable for experiments involving rice plants exposed to iron and zinc deficiency growth conditions and RNA from different plant parts including flag leaves, roots and grains were studied. The workflow itself is generic and could be conveniently extended

Fig. 1 Schematic workflow of reference genes identification and selection

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to other sets of conditions and/or samples. As a first step, we used the “RefGenes” module of the Genevestigator® toolbox [9], which offers a rapid and robust way to access gene expression data of different species, to search for candidate reference genes. After the selection of candidate reference genes, which were reportedly stably expressed over different conditions and tissues, suitable primers were designed for the qRT-PCR analysis. Subsequently, qRT-PCR analysis was run using TaqMan hydrolysis probes. Checking the stability of the gene expression is important, which is typically analyzed by using statistical algorithms such as the ΔCt approach, BestKeeper tool, geNorm tool, and NormFinder tool [10–13]. The ΔCt method computes the ΔCt value between one reference gene and the other reference genes in pair across all samples. Standard deviation (SD) is calculated for all gene pairs and the mean of the standard deviation shows the expression stability of one particular reference gene. Genes with a lower mean of the standard deviation has less variation in expression and therefore is considered relatively stable [10]. BestKeeper is an Excel-based tool. It evaluates the stability of potential reference genes by calculating the standard deviation and coefficient of variance (CV) of untransformed Cq values. The most stably expressed gene shows the lowest SD and CV value [11]. The geNorm tool was originally published as an Excel-based software. It calculates expression stability (Mvalue) of one gene based on the average pairwise variation across all putative reference genes. The lower M-value indicates more stable expression of the gene [12]. NormFinder is also an Excel add-in software, which evaluates putative reference genes based on a mathematical model. It estimates the expression variation across all samples as well as subgroups of samples and calculates stability value (SV) for candidate reference genes. According to NormFinder, the genes with lower SV are more stable [13]. In the end, results from all algorithms are finally examined to select appropriate reference genes across all samples.

2 2.1

Materials Plant Material

In our experiment, high grain iron and zinc containing transgenic rice line and its nontransgenic siblings were cultivated in irondeficient, zinc-deficient, and iron/zinc-sufficient hydroponic systems under greenhouse conditions. Flag leaves, roots, and grains with three biological replicates were sampled at three different grain filling stages: milky stage, dough stage, and mature stage (parameters as defined in the Rice Knowledge Bank, IRRI, Philippines). The aim was to identify best reference genes that are stable across genotypic background, different iron/zinc treatments, three different plant parts, and three different growth stages.

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2.2 Total RNA Extraction from Rice Roots and Flag Leaves

1. Liquid nitrogen. 2. Autoclaved mortars and pestles. 3. Refrigerated microcentrifuge. 4. Vortexer. 5. Magnetic mixer. 6. 1.5 mL RNase-free Eppendorf (EP) tubes. 7. RNase-free pipette tips. 8. Icebox and ice. 9. TRIzol® Reagent. 10. Chloroform. 11. Isopropanol. 12. 0.1% Diethyl pyrocarbonate (DEPC)-treated water: Add 0.5 mL DEPC to 500 mL ultrapure water, mix overnight with magnetic mixer and autoclave. Autoclaving will inactivate DEPC (see Note 1). 13. 2 M DEPC-treated NaCl solution: Dissolve 11.7 g NaCl in 70 mL ultrapure water, add ultrapure water to 100 mL. Add 100 μL DEPC to the prepared 100 mL 2 M NaCl solution, mix overnight with magnetic mixer and autoclave. 14. 70% ethanol: Mix 70 mL absolute alcohol and 30 mL DEPCtreated water.

2.3 Total RNA Extraction from Rice Grains

1. Liquid nitrogen. 2. Autoclaved mortars and pestles. 3. Refrigerated microcentrifuge. 4. Vortexer. 5. Magnetic mixer. 6. 2.0 mL RNase-free Eppendorf (EP) tubes. 7. RNase-free pipette tips. 8. Icebox and ice. 9. PCI (Phenol: Chloroform: Isoamyl Alcohol 25: 24: 1). 10. 0.1% diethyl pyrocarbonate (DEPC)-treated water (see above). 11. Absolute ethanol. 12. 70% ethanol (see above). 13. 3 M sodium acetate (pH 5.2) solution: Dissolve 12.3 g NaOAc to 30 mL ultrapure water. Adjust pH with glacial acetic acid to pH 5.2. Add ultrapure water to 50 mL. Add 50 μL DEPC to the prepared 50 mL 3 M NaOAc solution, mix overnight with magnetic mixer and autoclave. 14. 2 M DEPC-treated NaCl solution (see above).

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15. 1 M Tris–HCl (pH 9.0) buffer: Weigh 3.6 g Tris and mix with 20 mL DEPC-treated water in a beaker. Adjust pH with HCl to pH 9.0. Add DEPC-treated water and make up to 30 mL. Autoclave and store at 4
C. 16. 0.5 M EDTA stock solution: Weigh 5.58 g EDTA and mix with 30 mL DEPC-treated water in a beaker to dissolve. Autoclave and store at 4
C. 17. 5% sarcosyl (sodium N-Lauryl Sarcosine) stock solution: Mix 4.0 g sarcosyl with 50 mL DEPC-treated water, gradually add DEPC-treated water till sarcosyl is fully dissolved and make up the final volume to 80 mL. Autoclave and store at 4
C. 18. 10 M Guanidine hydrochloride stock solution: Weigh 38.2 g guanidine hydrochloride in a beaker and add 7 mL DEPCtreated water. Use magnetic stirrer to dissolve guanidine hydrochloride and gradually add DEPC-treated water till Guanidine hydrochloride is fully dissolved. Make up the final volume to 40 mL. Sterilize by filtration and store at 4
C (see Note 2). 19. 0.5 M 2-(N-morpholino) ethanesulfonic acid (MES) (pH 7.0) buffer: Weigh 1.95 g MES and dissolve in 15 mL DEPCtreated water in a beaker. Adjust pH with NaOH to pH 7.0. Add DEPC-treated water and make up to 20 mL. Sterilize by filtration and store at 4
C. 20. 10 mM DTT stock solution: Weigh 0.154 g DTT and dissolve in 100 mL DEPC-treated water. Sterilize by filtration and store at 4
C. 21. Extraction buffer (EB)–200 mL working solution. 50 mM Tris–HCl (pH 9.0): 10 mL 1 M Tris–HCl (pH 9.0) buffer. 150 mM NaCl: 15 mL 2 M DEPC-treated NaCl solution. 1% sarcosyl: 40 mL 5% sarcosyl stock solution. 20 mM EDTA: 8 mL 0.5 M EDTA stock solution. 5 mM DTT: 100 mL 10 mM DTT stock solution. DEPC-treated water: 27 mL. 22. Guanidine hydrochloride buffer (GB)–50 mL working solution. 8 M guanidine hydrochloride: 40 mL 10 M Guanidine hydrochloride stock solution. 20 mM EDTA: 8 mL 0.5 M EDTA stock solution. 20 mM MES (pH 7.0): 2 mL 0.5 M MES buffer. 200 mM 2-mercaptoethanol (BME): just before using, mix every 1.5 mL GB buffer with 21 μL 100% BME (see Note 1).

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2.4 DNase I Treatment and cDNA Synthesis

1. DNase I (Thermo Fisher Scientific Inc., USA).

2.5 Register and Install Genevestigator®

1. Register on Genevestigator® website: https://genevestigator. com/gv/ (see Note 3).

3

2. RevertAid™ first strand cDNA synthesis kit (Thermo Fisher Scientific Inc., USA).

2. Download and install Genevestigator® to local computer.

Methods

3.1 Total RNA Extraction from Rice Roots and Flag Leaves

1. Precool the mortar and pestle with liquid nitrogen and pulverize samples with the help of a pestle while using liquid nitrogen. 2. Transfer about 200 mg samples to 1.5 mL RNase-free Eppendorf (EP) tubes. 3. Add 1 mL TRIzol in each tube, vortex and mix the sample thoroughly (see Note 1). 4. Leave tubes in ice for 10 min (optional). 5. Centrifuge at 15,871  g for 15 min at 4
C. 6. Transfer the supernatant into new tubes without disturbing the plant debris. 7. Add 200 μL chloroform to the supernatant and vortex tube for 30 s (see Note 1). 8. Centrifuge at 15,871  g for 15 min at 4
C. 9. Transfer the upper layer into new tube without disturbing the interphase. 10. Add 250 μL isopropanol and 250 μL 2 M NaCl to each tube and vortex. 11. Leave tubes at room temperature for 10 min. 12. Centrifuge at 13,523  g for 10 min at 4
C. 13. Decant the supernatant and wash the pellet with 70% ethanol for three times. 14. Rinse pellet with absolute ethanol and dry it in fume hood for 5–10 min. 15. Add 50 μL DEPC-water to each tube to dissolve the pellet.

3.2 Total RNA Extraction from Rice Grains

RNA extraction from rice grains was slightly modified from the protocol described in Singh et al. [14] and was carried out as follows: 1. Grind the seed samples in liquid nitrogen using a mortar and a pestle. 2. Transfer 100 mg of the fine powder to a 2.0 mL RNase-free Eppendorf (EP) tube.

Selection of Suitable Reference Genes for qRT-PCR

299

3. Add 500 μL of extraction buffer, vortex vigorously, and mix with 500 μL of PCI (see Note 1). 4. Vortex and centrifuge at over 20,238  g at 4
C for 5 min. 5. Transfer the upper aqueous phase to a new 2.0 mL RNase-free Eppendorf tube, add 650 μL of GB and 350 μL of PCI, and vortex (see Note 1). 6. Centrifuge at over 20,238  g at 4
C for 5 min. 7. Transfer the upper aqueous phase to a new 2.0 mL RNase-free Eppendorf tube, add 500 μL of chloroform, and vortex (see Note 1). 8. Centrifuge at over 20,238  g at 4
C for 5 min. 9. Transfer the upper aqueous phase into two new 2.0 mL RNasefree Eppendorf tubes. 10. Add 45 μL 3 M NaOAc (pH 5.2) and 900 μL chilled absolute ethanol to each tube. 11. Incubate at 80
C for at least 90 min. 12. Spin the pellet over 20,238  g at 4
C for 20 min. 13. Wash the pellet with 70% chilled ethanol (V/V) for three times. Spin at 10,130  g at 4
C for 3 min. Discard the supernatant and dry the pellet at room temperature. 14. Dissolve RNA pellet in minimum amount of autoclaved DEPC water. Store at 80
C until further use (around 50 μL DEPC water could be added, depending on the size of the RNA pellet). 3.3 DNase I Treatment and cDNA Synthesis

1. Check RNA concentration (e.g., with a NanoDrop™). 2. Treat with DNase I to allow genomic DNA digestion. Follow the manufacturer’s’ instructions for reaction details. 3. cDNA synthesis. Carry out all the experimental steps following the manufacturer’s instructions.

3.4 Candidate Reference Genes Selection

1. In Genevestigator®, enter the “RefGenes” module. 2. Condition selection: Genevestigator® contains 2836 rice Affymetrix samples and 706 rice mRNA-seq samples (16.12.2018). Users could choose similar biological context as their own experiment conditions, such as genotypes, tissues and organs, development stages, or stress conditions (Fig. 2a, b). 3. List target genes: Users could enter a list of genes of interest in the “Gene Selection” window. The main window will demonstrate the expression range of genes of interest under the chosen experiment conditions (Fig. 2c). 4. Set the expression range of candidate reference genes according to the overall expression level of genes of interest.

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Meng Wang and Navreet K. Bhullar

Fig. 2 Candidate reference genes selection in Genevestigator®. (a) Choose species and database (Microarray or RNA-seq database). (b) Selection of reference genes according to the experiment condition, tissues, or growth stages. (c) Input target genes to view expression ranges. (d) Select reference genes according to the expression variation and expression range

5. Select stably expressed genes in the chosen expression range and biological context. Top 20 most stable transcripts will be listed and ranked according to their standard deviation (Fig. 2d). In our experiment, we chose 10 candidate reference genes considering different rice development stages, iron and zinc deficiency condition, and different tissues, that is, grains, roots, and flag leaves (Table 1). 3.5 Primer Designing for the Candidate Reference Genes

The qRT-PCR was carried out using Taqman hydrolysis probes (Roche, Switzerland) on 7500 FAST Real Time PCR system (Applied Biosystems, Inc., USA). We used Roche web tools for designing primers and selecting probes and the steps are described below: 1. Enter Roche Universal Probe Library Assay Design Center (https://lifescience.roche.com/en_cn/brands/universalprobe-library.html#assay-design-center).

gaagtgatgctgccgttgta cttcgaagcgagggaattta gcaaatagctaagccgtctctc

74 7 96

4 11 9

LOC_Os11g43970 AAA-type ATPase family protein, putative, expressed

LOC_Os06g01700 CWC15 homolog A, putative, expressed

LOC_Os02g51850 OsAPRL3 adenosine 5’-phosphosulfate reductase-like 72 OsAPRL3, expressed 59

LOC_Os05g48960 U2 snRNP auxiliary factor, small subunit

LOC_Os02g54990 TMS membrane protein/tumor differentially expressed protein, putative, expressed

LOC_Os04g40950 Glyceraldehyde-3-phosphate dehydrogenase, putative, expressed (OsGAPDH)

LOC_Os02g05330 DEAD-box ATP-dependent RNA helicase, putative, expressed (OseIF-4a)

LOC_Os03g50885 OsActin1 (OsActin1)

1.95

2.00

2.00

1.96

ggggacagtgtggctgac

gacctggatctttggtggaa

agagacatccacggttggaa

1.90

1.96

1.98

cagactcgataaccatgacacg 1.91

acttggaagcccaagcagt

gaaacacagcgatctcagaca

acgatggaggacgaaggtag 1.99

ttccctgactgggctcct

cacgcccttcaacactgag

2.00

Amplification efficiency

The gene ID for candidate reference genes, gene annotation, TaqMan probe number, forward and reverse primers used for the qRT-PCR, and amplification efficiency for each pair of primer is shown

gccgtcctctctctgtatgc

agatgctctcccgtggttt

caacatcatccctagcagca

tcgctataccacccctcttg

gtggtggtggtggtggac

agcagctgaaagcaccaaa

124

Reverse primer 50 –30

caatgagtaccaggaagcactg gaaagagctttgcacccaag

Forward primer 50 –30

LOC_Os01g05420 IWS1 C-terminus family protein, putative, expressed

TaqMan probe 88

Gene annotation

LOC_Os02g25840 Conserved oligomeric Golgi complex component 4, related, putative, expressed

Gene ID

Table 1 Information on candidate reference genes that were studied in rice

Selection of Suitable Reference Genes for qRT-PCR 301

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Meng Wang and Navreet K. Bhullar

2. Select target organism: Oryza sativa (Rice). 3. Specify the target by providing sequence ID, gene name, keyword, or fasta sequence. 4. The website suggests primers sequences and hydrolysis probes. In Table 1, we listed all the primers sequences and hydrolysis probes used in our experiment. 3.6 Evaluation of qRT-PCR Amplification Efficiency

1. Pool equal volume of each cDNA sample and make a serial dilution (2:1, 1:1, 1:10, 1:100, 1:1000, 1: 10000) of the mixed cDNA. Set the cDNA concentration of 1:10000 as 1, then the cDNA concentration of the serial dilution is 20,000, 10,000, 1000, 100, 10, and 1, respectively. 2. Perform qRT-PCR with at least two technical replicates at each dilution point and collect Ct values. The composition and reaction conditions are provided in Tables 2 and 3, respectively. 3. Construct a standard curve of Ct value vs. log10 transformed of cDNA concentration (4.301, 4, 3, 2,1, 0) (Fig. 3). 4. Determine the slope of each standard curve. 5. Calculate qRT-PCR amplification efficiency from the equation: E ¼ 10(1/slope) for each primer pair (Table 1).

3.7 qRT-PCR to Obtain Ct Values for Candidate Reference Genes

1. Total volume of the qRT-PCR reaction mixture is 25 μL. The composition and reaction conditions are given in Tables 2 and 3, respectively. The reaction was performed on two technical replicates for each sample as well as a water control. 2. The raw Ct values were collected from the qRT-PCR machine for data analysis. Ct values from technical replicates are averaged and used for further analysis. Table 2 qRT-PCR reaction composition Composition

Volume (μL)

Mastermix

12.5

cDNA

1

Forward primer

2.25 (10 μM)

Reverse primer

2.25 (10 μM)

Probe

0.25

H2O

6.75

Total

25

Selection of Suitable Reference Genes for qRT-PCR

303

Table 3 qRT-PCR reaction conditions Step

Temperature (
C)

Time

Incubation

50

2 min

Initialization

95

10 min

Denaturation Annealing and extension

95 60

15 s 1 min

]40 cycles

Fig. 3 Standard curve for calculation of PCR amplification efficiency. x-axis: log10 transformed cDNA concentration, y-axis: Ct value collected at each cDNA concentration. The slope of the regression is used to estimate the PCR amplification efficiency

3.8 Evaluation of Expression Stability of Candidate Reference Genes by ΔCt Approach

1. Calculate ΔCt of one reference gene verses other reference genes among all samples. 2. Calculate standard deviation of ΔCt for this gene verses each reference gene. 3. Calculate mean of standard deviation, which demonstrates the expression variability of one gene against other reference genes in all the sample set (Table 4). 4. Carry out this workflow for all the reference genes and get the mean of standard deviation for each candidate reference gene. Genes with lower mean of standard deviation are more stable across the tested samples.

1.4753

0.8053

1.5086

Roots 5

Roots 6

Roots 7

1.3837

Flag Leaves 9

0.737

0.99455

Flag Leaves 8

Roots 4

1.9053

Flag Leaves 7

0.8895

2.0588

Flag Leaves 6

Roots 3

1.9164

Flag Leaves 5

0.68645

1.8679

Flag Leaves 4

Roots 2

2.7071

Flag Leaves 3

0.53775

2.31475

Flag Leaves 2

Roots 1

2.7042

2.43425 1.1987 1.7232

1.62415

1.56135

4.4173

3.62645

1.96715

0.9407

0.79275

0.98355

1.30345

1.00335

2.75475

3.24595

3.22175

2.6436

3.10585 2.1658

1.01985

2.75495

2.9284

1.48305

0.28895

2.22895

1.7279

1.1735

2.12485

1.31125

2.0128

2.258

1.36455

2.62085

1.5729

2.2062

1.456

1.6202

1.3677

1.2709

1.42315

1.0352

1.883

2.9731

2.86645

2.0143

3.9251

3.00175

3.16235

1.4254

0.1635

0.68755

0.0069

0.0743

0.06485

0.07095

1.30435

0.58685

1.88585

2.22515

2.1616

1.68095

3.5042

3.0569

2.8608

4.04235

2.5881

3.14215

2.40795

2.69555

2.6248

2.32055

3.0487

2.55715

4.0045

3.3491

3.49385

3.1987

4.25845

3.90805

3.98245

4.4067

3.0349

3.81245

3.2981

3.39615

2.1051

2.3145

3.32825

3.25135

3.3222

3.19675

3.2805

3.6332

4.07505

3.6117

3.6997

1.784

1.23235

1.4313

1.42325

1.36885

1.53205

1.3473

1.72815

1.33925

1.5341

1.13455

1.4547

1.6678

1.50465

1.6519

1.495

0.953

0.9932

1.6604

1.3486

1.83255

0.08065

0.5532

0.4367

0.30385

0.06305

0.09665

0.4783

0.5588

0.57725

0.57985

0.56375

Mean LOC_Os01g05420 LOC_Os05g48960 LOC_Os11g43970 LOC_Os06g01700 LOC_Os02g51850 LOC_Os02g54990 LOC_Os04g40950 LOC_Os02g05330 LOC_Os03g50885 StdDev

Flag Leaves 1

Tissues

ΔCt: LOC_Os02g25840 vs. other candidate genes

Table 4 Calculate mean of standard deviation of ΔCt for one reference gene verses other candidate genes

1.2936

1.05625

1.39425

0.87895

1.04455

12.27535

1.31465

0.19595

0.45145

1.0425

2.4995

Roots 9

Grains 1

Grains 2

Grains 3

Grains 4

Grains 5

Grains 6

Grains 7

Grains 8

Grains 9

StdDev

2.01565

2.6542

3.2612

2.7671

1.57195

1.00565

2.385

2.3389

1.2332

1.107

1.52565

2.0217

2.29105

3.23345

2.24065

1.54095

12.0236

1.7453

2.07445

7.58115

0.34335

7.659

1.1849

8.18935

2.4848

2.6796

2.0979

1.3643

1.8114

12.6011

2.7972

2.1689

3.673

3.17115

2.12365

9.27995

2.5284

0.64265

0.2101

0.58245

0.83815

11.6121

0.493

0.30305

1.16885

0.8372

0.9814

7.53595

2.3227

3.63175

2.7793

1.48205

0.80115

11.70335

3.22305

2.7544

3.867

3.26735

3.9058

10.81185

2.5165

2.5739

1.7551

1.2029

1.1804

12.412

2.9192

1.984

3.69895

3.4057

4.17075

11.4802

2.6105

1.35455

1.11145

0.9941

0.40355

12.20565

1.2015

0.86895

0.93895

1.41085

1.42025

9.7298

2.4829

1.87825

1.81525

0.25645

0.29005

11.4951

1.6535

1.2385

1.8266

2.40405

0.31215

7.6861

2.5657

This table takes LOC_Os02g25840 as an example, calculating ΔCt between the LOC_Os02g25840 and other candidate genes. The standard deviation of ΔCt for each gene pair is calculated and then averaged to get the mean of standard deviation

7.89485

Roots 8

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Meng Wang and Navreet K. Bhullar

Fig. 4 Workflow of selecting reference genes by BestKeeper. (a) Input primer efficiency in the Intro worksheet. (b) Input Ct values in HKG vs. BK worksheet (partial data is shown in b). (c) Rank the most stably expressed genes according to CV and SD value 3.9 Evaluation of Expression Stability of Candidate Reference Genes by BestKeeper

1. Open the BestKeeper workbook and enable macros.

3.10 Evaluation of Expression Stability of Candidate Reference Genes by geNorm

1. Convert Ct values to relative quantities: normalize data to the lowest Ct value for each candidate reference gene (Table 5).

3.11 Evaluation of Expression Stability of Candidate Reference Genes by NormFinder

2. Input primer efficiency in the Intro worksheet (Fig. 4a). 3. Input Ct values in HKG vs. BK worksheet (Fig. 4b). 4. Get CV [% CP] and std. dev [CP] values of each reference genes. The most stably expressed genes show the lowest CV and SD value (Fig. 4c).

2. Run geNorm add-in excel sheet and enable macros. 3. Input the data. 4. Click the “Calculate” button, and then click the “automated analysis” button. Two charts will be generated. One chart is a line plot which ranks the most two stable reference genes (Fig. 5a). Genes with lower average expression stability M value are considered as stably expressed across the samples. The other chart is a bar plot and determines the optimal number of reference genes for normalization (Fig. 5b). 1. Similar to geNorm, convert Ct values to relative quantities. Input gene IDs/names in the first column, sample names in the first row, and mark sample groups in the last row (Fig. 6a). 2. Run NormFinder Excel add-in file and enable Macros. NormFinder will appear in the menu bar. Click NormFinder and a dialogue box will appear.

0.16378215

0.28446045

0.34300464

0.60455689

0.40390838

Flag Leaves 5

Flag Leaves 6

Flag Leaves 7

Flag Leaves 8

Flag Leaves 9

0.75990975

0.36437604

Flag Leaves 4

Roots 2

0.1772245

Flag Leaves 3

1

0.19509517

Flag Leaves 2

Roots 1

0.46456424

0.40393638

0.4794991

0.34811841

0.39786475

0.4243863

0.39146358

0.2042064

0.43929135

0.38225307

0.32060082

1

0.06245587

0.08135757

0.94746942

1

0.70062247

0.04100638

0.00795425

0.01013499

0.03408438

0.04418673

0.0983715

0.65840267

0.91310666

0.51059942

0.33504838

0.35083328

0.39727259

0.24584901

0.37904596

0.43368802

0.38559671

1

0.48193652

0.58947051

0.27084221

0.3085921

0.31491716

0.54685921

0.29780986

0.36479954

0.65553322

0.38658656

1

0.23553282

0.28210419

0.29559628

0.26906936

0.37563412

0.39411812

0.21714039

0.34620537

0.59588259

0.4810971

1

0.65761951

0.69789101

0.47957718

0.50843545

0.76419208

0.41988877

0.27541324

0.48001185

0.4862331

0.42395685

1

0.34796344

0.52621641

0.43042781

0.60771703

0.3648815

0.27850667

0.17116001

0.4789431

0.31833042

0.25499762

0.63676396

0.86742449

1

0.53587563

0.61017557

0.40127097

0.25571587

0.18559066

0.46558299

0.20721112

0.2511623

0.52470644

(continued)

0.27589929

0.48182564

0.19312268

0.25762834

0.13060112

0.11221465

0.08598497

0.18986561

0.09856606

0.10791638

0.2385148

LOC_Os02g25840 LOC_Os01g05420 LOC_Os05g48960 LOC_Os11g43970 LOC_Os06g01700 LOC_Os02g51850 LOC_Os02g54990 LOC_Os04g40950 LOC_Os02g05330 LOC_Os03g50885

Flag Leaves 1

Calculate

Table 5 Convert Ct values to relative quantities to input data into geNorm

0.10487553

0.09748

0.43232854

0.81346377

0.23110975

0.00227211

0.35945922

0.16584415

0.16584415

0.16584415

0.15393039

5.9533E  05

0.09394759

0.23195229

0.35302689

0.08183433

Roots 5

Roots 6

Roots 7

Roots 8

Roots 9

Grains 1

Grains 2

Grains 3

Grains 4

Grains 5

Grains 6

Grains 7

Grains 8

Grains 9

0.29149097

0.53662789

0.24529018

0.00605366

0.00687564

0.01434257

0.02269697

0.02269697

0.02269697

0.4216681

0.34483578

0.88271709

0.05275189

0.03906695

0.04779692

0.05331858

0.18859074

0.37614879

0.22727642

0.12359323

0.11332852

0.28269667

0.25273618

0.25273618

0.25273618

0.20759189

0.20902532

0.46925731

0.73549046

0.48275167

0.70983306

0.70841794

0.13390065

0.37423586

0.15193358

0.08535889

0.09543116

0.26763532

0.37005367

0.37005367

0.37005367

0.3875112

0.35045787

0.35265805

0.59111903

0.49004706

0.53483087

0.67782851

0.03785821

0.12101015

0.10292034

0.0497693

0.0552225

0.06419479

0.0877991

0.0877991

0.0877991

0.21030426

0.12495236

0.18393909

0.26997543

0.20632635

0.23692462

0.25511153

0.15755236

0.35526906

0.10367993

0.02870117

0.03436348

0.21813657

0.24065972

0.24065972

0.24065972

0.7489665

0.57831101

0.54168772

0.68434058

0.54286326

0.596633

0.81159364

0.053311

0.12869873

0.05834337

0.02357734

0.03570782

0.12579566

0.1887555

0.1887555

0.1887555

0.68224704

0.68402029

0.51866855

0.70229611

0.64069076

0.8225619

1

0.08845825

0.3104981

0.19084032

0.05333418

0.11784933

0.1473669

0.18239625

0.18239625

0.18239625

0.38897429

0.76439311

0.32358536

0.75745475

0.46878976

0.84305253

0.92229705

0.11107883

0.41301057

0.102927

0.03138511

0.0661321

0.17260975

0.29940827

0.29940827

0.29940827

0.16003986

0.16721184

0.16041009

0.52785511

0.45111761

0.64970976

1

Expression of the lowest Ct value for each candidate reference gene is set as 1. Other Ct values are then converted to relative quantities by normalizing expression to sample with the lowest Ct value

0.05567602

0.15944713

0.08775955

0.07718691

0.11391266

0.11391266

0.11391266

0.29105223

0.17861808

0.2172006

0.4695335

0.39703828

0.43805988

0.79572951

Roots 4

0.55463094

0.906419

LOC_Os02g25840 LOC_Os01g05420 LOC_Os05g48960 LOC_Os11g43970 LOC_Os06g01700 LOC_Os02g51850 LOC_Os02g54990 LOC_Os04g40950 LOC_Os02g05330 LOC_Os03g50885

Roots 3

Calculate

Table 5 (continued)

Selection of Suitable Reference Genes for qRT-PCR

309

Fig. 5 Evaluation of expression stability of candidate reference genes by geNorm. (a) Line plot ranks the expression stability of reference genes. (b) Bar plot indicates the number of reference genes for qRT-PCR

3. Select data input area and check first three boxes in the dialogue box. If the input data is not log transformed (natural base (e) logarithm), also tick the fourth box (Fig. 6b). 4. If the fifth box is checked, the result will be a simple report of stability values, best reference gene and best combination of reference genes. By unchecking the fifth box, the results will be

310

Meng Wang and Navreet K. Bhullar

Fig. 6 Evaluation of expression stability of candidate reference genes by NormFinder. (a) Convert Ct values to relative quantities (partial data is shown in a). (b) Dialogue box for selecting data input area, data formatting, and output choices. (c) Output of results when unchecking the fifth box in the dialogue box

more detailed with intra and inter group gene expression stability analysis (Fig. 6c). The expression of genes with lower stability values are more stable. 3.12 Determine the Best Reference Genes According to the Four Algorithms

4

The above four algorithms are based on different models; therefore, the obtained results are slightly different. In this case, the researchers need to make a comprehensive consideration of their sample types, experiment conditions, and number of reference genes they could include in their experiment (see Note 4).

Notes 1. This step should be carried out in a fume hood. 2. While preparing the 10 M guanidine hydrochloride stock solution, first only add 7 mL water to guanidine hydrochloride and use magnetic stirrer to dissolve. Only if necessary, add additional water to make the total volume of 40 mL. The final volume of the 10 M guanidine hydrochloride stock solution

Selection of Suitable Reference Genes for qRT-PCR

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might be a bit higher than 40 mL. This does not affect its function and can be used further. 3. Genevestigator® is not a free software. However, it allows 7 days free trial with full access to all functions. Besides, the protocol described here could also be used to assess the expression stability of candidate genes selected from literature or other sources. 4. The example we described here shows comprehensive results of all the tested plant samples—across treatments and development stages. Reference genes suited to individual tissues and/or development stages and/or treatment can be identified in a similar manner.

Acknowledgments This research was supported by funds from State Secretariat for Education, Research and Innovation to N.K.B. We thank Prof. Gruissem for providing access to Lab infrastructure. We thank Irene Zurkirchen for the technical support in the greenhouse. Conflict of Interest Statement: None declared. References 1. Gachon C, Mingam A, Charrier B (2004) Realtime PCR: what relevance to plant studies? J Exp Bot 55(402):1445–1454. https://doi. org/10.1093/jxb/erh181 2. Bustin SA, Benes V, Nolan T, Pfaffl MW (2005) Quantitative real-time RT-PCR—a perspective. J Mol Endocrinol 34(3):597–601. https://doi.org/10.1677/jme.1.01755 3. Nolan T, Hands RE, Bustin SA (2006) Quantification of mRNA using real-time RT-PCR. Nat Protoc 1(3):1559–1582. https://doi.org/ 10.1038/nprot.2006.236 4. Radonic A, Thulke S, Mackay IM, Landt O, Siegert W, Nitsche A (2004) Guideline to reference gene selection for quantitative real-time PCR. Biochem Biophys Res Commun 313 (4):856–862. https://doi.org/10.1016/j. bbrc.2003.11.177 5. Gutierrez L, Mauriat M, Guenin S, Pelloux J, Lefebvre JF, Louvet R, Rusterucci C, Moritz T, Guerineau F, Bellini C, Van Wuytswinkel O (2008) The lack of a systematic validation of reference genes: a serious pitfall undervalued in reverse transcription-polymerase chain reaction (RT-PCR) analysis in plants. Plant Biotechnol J 6(6):609–618. https://doi.org/10.1111/j. 1467-7652.2008.00346.x

6. Schmittgen TD, Zakrajsek BA (2000) Effect of experimental treatment on housekeeping gene expression: validation by real-time, quantitative RT-PCR. J Biochem Biophys Methods 46 (1–2):69–81. https://doi.org/10.1016/ S0165-022x(00)00129-9 7. Carmona R, Arroyo M, Jimenez-Quesada MJ, Seoane P, Zafra A, Larrosa R, Alche JD, Claros MG (2017) Automated identification of reference genes based on RNA-seq data. Biomed Eng Online 16:65. https://doi.org/10. 1186/s12938-017-0356-5 8. Czechowski T, Stitt M, Altmann T, Udvardi MK, Scheible WR (2005) Genome-wide identification and testing of superior reference genes for transcript normalization in Arabidopsis. Plant Physiol 139(1):5–17. https://doi. org/10.1104/pp.105.063743 9. Hruz T, Wyss M, Docquier M, Pfaffl MW, Masanetz S, Borghi L, Verbrugghe P, Kalaydjieva L, Bleuler S, Laule O, Descombes P, Gruissem W, Zimmermann P (2011) RefGenes: identification of reliable and condition specific reference genes for RT-qPCR data normalization. BMC Genomics 12:156. https://doi.org/10.1186/14712164-12-156

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10. Silver N, Best S, Jiang J, Thein SL (2006) Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR. BMC Mol Biol 7:33. https://doi.org/10.1186/1471-2199-7-33 11. Pfaffl MW, Tichopad A, Prgomet C, Neuvians TP (2004) Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper—excel-based tool using pair-wise correlations. Biotechnol Lett 26(6):509–515. https://doi.org/10.1023/B:Bile. 0000019559.84305.47 12. Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric

averaging of multiple internal control genes. Genome Biol 3(7). https://doi.org/10. 1186/gb-2002-3-7-research0034 13. Andersen CL, Jensen JL, Orntoft TF (2004) Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Res 64 (15):5245–5250. https://doi.org/10.1158/ 0008-5472.Can-04-0496 14. Singh G, Kumar S, Singh P (2003) A quick method to isolate RNA from wheat and other carbohydrate-rich seeds. Plant Mol Biol Report 21(1):93–93. https://doi.org/10.1007/ bf02773401

Chapter 21 Rice Protoplast Isolation and Transfection for Transient Gene Expression Analysis Jennylyn L. Trinidad, Toshisangba Longkumer, and Ajay Kohli Abstract Protoplasts are a versatile and powerful cell-based system to study different plant processes in vivo, due to their ability to maintain cell identity and carry out reactions and metabolic processes similar to intact plants. In rice, despite numerous reports, difficulties are encountered in protoplast isolation and transfection. These include insufficient numbers of protoplasts isolated and inefficient transfection. Such difficulties limit the use of this simple yet useful technology. The need to use protoplasts is particularly important when similar experiments may not work in yeast or Pichia, due to differences in functionally essential protein posttranslation modifications. In this chapter, we describe a rice protoplast isolation and transfection method. Key words Rice, Protoplast, Transient gene expression, Transfection

1

Introduction A plant protoplast isolation method was first described by Cocking [1]; from then on, protoplasts have been utilized in the study of several plant processes. They are ideal to use in studying membrane transporters, ion channels, and calcium signaling and regulation because they retain cell membrane potentials similar to intact cells [2]. The subsequent development of methods enabling the introduction of DNA, RNA, and proteins into protoplasts using various methods such as PEG [3], electroporation [4], and microinjection [5] contributed in the usefulness of protoplasts in the study of plant gene regulation and signal transduction [2]. Protoplasts are a suitable transient expression system because they retain their cell identity and differentiated state. They also demonstrated high transformation efficiency (up to 90%) and are relatively low maintenance [6]. Being an active and homogeneous cell population, protoplasts are ideal for synchronous treatments and experiments and can be useful for high-throughput functional screening of candidate genes. More importantly, protoplasts, having retained

Anindya Bandyopadhyay and Roger Thilmony (eds.), Rice Genome Engineering and Gene Editing: Methods and Protocols, Methods in Molecular Biology, vol. 2238, https://doi.org/10.1007/978-1-0716-1068-8_21, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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their identity, show similar reactions to those of intact cells in response to hormones, metabolites, environmental stimuli, and pathogen-derived elicitors [2]. Protoplasts can be advantageous in situations when either overexpression or deletion of a gene is lethal in intact plants. In practical terms, protoplasts are favorable since plant materials grown from seeds are genetically stable, and they are also easily stored without requiring sub-culturing and sterile tissue culture practices and facilities. In addition, multiple plasmids with different constructs can be co-transfected [2], with relatively high efficiency [7]. A protoplast transient assay system is useful in dissecting a broad range of plant signal transduction pathways and transcriptional regulatory networks [8]. It is a convenient alternative to producing transgenic plants, which is expensive and timeconsuming especially when used for large-scale analyses. Another advantage of the protoplast system is that gene activity can be measured easily and just after DNA delivery [9]. Transient expression in mesophyll protoplasts has been used to elucidate molecular mechanisms underlying auxin signaling and responses [10, 11], to study abiotic stress signaling via MAPK cascades [12, 13], cytokinin [14], CDPK, and ABA signal transduction [2, 15]. The protoplast system has not been widely used in rice due to difficulties in efficiently isolating protoplasts from leaves. Chen et al. [7] reported that isolating protoplasts from the stem and sheath of 2-week-old rice seedlings would yield up to 2
106 cells, which is a 40 times higher yield than the cells isolated from leaves. More recently, Zhang et al. [16] simplified the protoplast isolation method from rice green tissue. The cells obtained were found suitable for transfection with multiple constructs and showed simultaneous transgene expression. Subsequently, protein immunoblot, localization, and protein-protein interaction assays were performed. The impetus for rice protoplast isolation in our lab was to test the hypothesis that protein post-translational modification for a rice transcription factor shown to be useful for yield under drought [17] can vary between yeast and rice. Such a variation in turn can affect protein function, leading to a lack of transactivation by a rice transcription factor in yeast, when that same factor has that function in rice. As a prelude to testing this hypothesis, our attempts at rice protoplast isolation yielded dismal results. Thus, we developed and standardized the following reliable protocol for rice protoplast isolation and reporter gene transfection.

2

Materials Solutions are prepared using sterilized nanopure water and molecular biology-grade reagents. Storage temperatures are indicated for each prepared reagent. All buffers described below are summarized in Tables 1 and 2. All equipment and materials required are listed in Table 3.

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Table 1 List of reagents for protoplast isolation Half strength MS medium (1000 ml) MS basal medium

2.2 g

Gelzan™; Sigma-Aldrich Cat. No. G1910

2.5 g

Nanopure water

To 1 l 

Sterilize by autoclaving at 121 C for 20 min; store at 4  C Sterilizing solutions (100 ml) Ethanol (75% v/v)

75 ml ethanol +25 ml sterile nanopure water

Sodium hypochlorite/bleach solution (50% v/v)

50 ml bleach +50 ml sterile nanopure water +1 drop Tween 20

Protoplast isolation buffer/enzyme solution (10 ml) Cellulase RS (1.5%)

0.15 g

Macerozyme R-10 (0.75 g)

0.075 g

Mannitol (0.6 M)

1.093 g

MES (10 mM)

1.0 ml from 100 mM stock

BSA (0.1%)

0.1 g

Sterile nanopure water

To 10 ml

Filter-sterilize; store at 20  C W5 buffer (500 ml) NaCl (154 mM)

4.5 g

CaCl2 (125 mM)

6.95 g

KCl (5 mM)

25 ml from 100 mM stock

MES (2 mM)

10 ml from 100 mM stock

Sterile distilled water

To 500 ml

Adjust pH to 5.7 with KOH, filter-sterilize, and store at 4  C MMG buffer (500 ml) Mannitol (0.4 M)

36.45 g

MgCl2 (15 mM)

75 ml from 100 mM stock

MES (4 mM)

20 ml from 100 mM stock

Sterile distilled water

To 500 ml

Adjust pH to 5.7 with KOH, filter-sterilize, and store at 4  C

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Table 2 List of reagents for protoplast transfection PEG-calcium transfection buffer (10 ml) Mannitol (0.6 M)

1.093 g

CaCl2 (100 mM)

0.111 g

PEG4000 (40%)

4.0 g

Sterile distilled water

To 10 ml

Adjust pH to 7.5–8.0 using KOH, aliquot to 1.5 ml tubes, and store at 20  C W1 buffer (100 ml) Mannitol (0.5 M)

9.11 g

MES (4 mM)

4 ml from 100 mM stock solution

KCl (20 mM)

20 ml from 100 mM stock solution

Sterile distilled water

To 100 ml 

Adjust pH to 5.7, filter-sterilize, and store at 4 C Stock solutions 100 mM MES (500 ml) 2-(N-Morpholino)ethanesulfonic acid

9.76 g

Sterile distilled water

To 500 ml

Filter-sterilize and store at 4  C 100 mM MgCl2 (500 ml) Magnesium chloride (MgCl2)

4.76 g

Sterile distilled water

To 500 ml

Filter-sterilize and store at 4  C 100 mM KCl (500 ml) Potassium chloride (KCl)

3.73 g

Sterile distilled water

To 500 ml

Filter-sterilize and store at 4  C 100 mM CaCl2 (500 ml) CaCl2

5.55 g

Sterile distilled water

To 500 ml

Filter-sterilize and store at 4  C

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Table 3 List of equipment and materials for protoplast isolation and transfection Equipment

Consumables

Rotary shaker

Sterilized filter papers

Incubator (set to 28  C)

Sterilized petri dish

Centrifuge with swinging bucket rotor

Razor blades

Water bath

15 ml polypropylene tubes

Vacuum desiccator

50 ml polypropylene tubes

Hemocytometer

Nylon mesh strainer (40 μm)

Imaging software Fluorescence microscope, with optical filter sets

2.1 Rice Seedling Growth Medium

2.2 Seed Sterilization Solutions

Solidified half (1/2) strength Murashige and Skoog (MS) medium: For 1 l of medium, add 2.2 g of MS basal medium (see Note 1) and 2.5 g of solidifying agent (Gelzan™; Sigma-Aldrich Cat. No. G1910) in 1 l of water in a beaker. Mix thoroughly and then divide into four 1 l beakers (250 ml each), cover with aluminum foil, and sterilize by autoclaving at 15 psi for 20 min (see Note 2). Let cool completely and allow to solidify. Growth medium can be stored for up to 2 weeks at 4  C. 1. Ethanol: 75% solution in sterile nanopure water. Store at room temperature. 2. Sodium hypochlorite solution: 50% bleach in sterile nanopure water. Add one drop of Tween 20 and mix thoroughly. Store at room temperature.

2.3 Protoplast Isolation

1. 2-(N-Morpholino)ethanesulfonic acid (MES; 100 mM): In a large beaker or graduated cylinder, add 400 ml of sterile nanopure water. Weigh 9.76 g MES and transfer to the beaker and mix thoroughly. Make up the volume to 500 ml. Filter-sterilize using a vacuum or syringe filter (filter pore size; 0.2 μm). Store at 4  C. 2. Magnesium chloride (MgCl2; 100 mM): Add 400 ml of sterile nanopure water into a large beaker or graduated cylinder. Weigh 4.76 g MgCl2 and transfer to the beaker and mix thoroughly. Make up the volume to 500 ml. Filter-sterilize using a vacuum or syringe filter (filter pore size; 0.2 μm). Store at 4  C. 3. Potassium chloride (KCl; 100 mM): In a large beaker or graduated cylinder, add about 400 ml of sterile nanopure water. Weigh 3.73 g KCl and transfer to the beaker and mix

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thoroughly. Make up the volume to 500 ml. Filter-sterilize using a vacuum or syringe filter (filter pore size; 0.2 μm). Store at 4  C. 4. Calcium chloride (CaCl2; 100 mM): Add about 400 ml of sterile nanopure water into a large beaker or graduated cylinder. Weigh 5.55 g CaCl2 and transfer to the beaker and mix thoroughly. Make up the volume to 500 ml. Filter-sterilize using a vacuum or syringe filter (filter pore size; 0.2 μm). Store at 4  C. 5. Enzyme solution/protoplast isolation buffer: In a 50 ml polypropylene tube, add about 5 ml of sterile nanopure water. Add 1.0 ml of 100 mM MES, 1.0 ml of 100 mM CaCl2, 1.093 g of mannitol, and 0.1 g bovine serum albumin (BSA). Fill up volume to 10 ml and filter-sterilize (0.2 μm filter pore size). Prior to use, heat the solution to 55  C for 10 min, and cool slightly by placing in an ice bath. Add 0.15 g of Cellulase Onozuka RS and 0.075 g Macerozyme R-10 and mix thoroughly (see Note 3). 6. W5 buffer: Add about 300 ml sterile nanopure water in a large beaker or graduated cylinder. Weigh 4.5 g NaCl, and 6.95 g CaCl2 and transfer to the beaker and mix thoroughly. Add 25 ml of 100 mM KCl and 10 ml 100 mM MES. Adjust pH to 5.7 with 1 N KOH, and then fill up volume to 500 ml. Filter-sterilize using a vacuum or syringe filter (filter pore size; 0.2 μm). Store at 4  C. 7. MMG buffer: Add about 300 ml sterile nanopure water in a large beaker or graduated cylinder. Weigh 36.45 g mannitol and transfer to the beaker and mix thoroughly. Add 75 ml of 100 mM MgCl2 and 20 ml 100 mM MES. Adjust pH to 5.7 with 1 N KOH, and then fill up volume to 500 ml. Filtersterilize using a vacuum or syringe filter (filter pore size; 0.2 μm). Store at 4  C. 2.4 Protoplast Transfection

1. PEG-calcium transfection buffer: Add about 5 ml sterile nanopure water in a 15 ml tube. Weigh 1.093 g mannitol and transfer to the beaker and mix thoroughly. Add 0.111 g of CaCl2 and 4.0 g polyethylene glycol (PEG) 4000 (see Note 4). Mix by inverting the tube until PEG4000 completely dissolves. Adjust pH to 7.5 to 8.0 with 1 N KOH; fill up volume to 10 ml. Aliquot to 1.5 ml tubes and store at 20  C. 2. W1 buffer: In a medium-sized beaker, add 50 ml sterile nanopure water. Weigh 9.11 g mannitol and transfer into the beaker; mix thoroughly. Add 4.0 ml of 100 mM MES and 20 ml 100 mM KCl. Adjust pH to 5.7; fill up volume to 100 ml. Filter-sterilize using a vacuum or syringe filter (filter pore size; 0.2 μm). Store at 4  C.

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Methods

3.1 Rice Seed Sterilization and Sowing in MS Growth Medium

1. De-hull 50–60 rice seeds using fine forceps. To account for loss during germination, this is a larger number of seeds than the number of seedlings finally required. Place seeds in a clean 50 ml tube and add 10 ml of 75% ethanol. Sterilize for 5 min under constant shaking at 80–100 rpm. 2. Remove ethanol and wash briefly with sterile nanopure water. 3. Add 10–15 ml of 2.5% sodium hypochlorite (bleach) solution, and incubate for 30 min under constant shaking at 80–100 rpm. 4. Remove sodium hypochlorite, and wash seeds with sterile nanopure water for at least five times, until all traces of the bleach solution are removed. 5. Under laminar flow, transfer seeds onto a petri dish lined with sterilized filter papers to dry the seeds. 6. Working aseptically, carefully transfer the seeds to the MS growth medium. Cover the beaker with foil or parafilm. 7. Grow at 30  C 8–11 days, the first 3–5 days under dark, and then transfer under light for the remaining days. If etiolated seedlings are needed, grow under dark throughout the 8–11day growing period (see Note 5).

3.2 Protoplast Isolation

1. Take 50 8–11-day-old rice seedlings and cut them into 0.5 mm strips using sharp razor blades. Cut both the leaf sheath and stem, making sure not to crush the tissues by changing the razor blades once dullness is felt during cutting. 2. Immediately place cut strips in a petri dish containing 10 ml protoplast isolation buffer. 3. Place the petri dish inside a desiccator and vacuum-infiltrate in the dark for 30 min. This facilitates enzyme penetration inside the tissues. 4. Incubate in the dark with gentle shaking (60–80 rpm) for 4–5 h at room temperature. 5. After digestion (see Note 6), add an equal volume of W5 buffer, followed by vigorous hand shaking for 10 s. 6. Release the protoplasts by filtering through 40 μM nylon mesh cell strainer into 50 ml tubes. Add more W5 buffer onto the tissues, and then wash and filter again. Repeat one more time. 7. Collect the protoplasts by centrifugation at 100
g for 3 min at 25  C using a swinging bucket rotor; set “deceleration” to off (see Note 7).

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8. Wash the protoplasts with 5 ml of W5 buffer and re-collect by spinning for 1 min at 100
g. 9. Remove the buffer; re-suspend the pellet in MMG buffer. 10. Keep the protoplasts in an ice bath or store at 4  C prior to transfection (see Note 8). 11. Determine cell count by diluting the protoplast suspension 5
and pipetting 9 μl of the suspension into a hemocytometer. View the cells under 100
magnification and count total cells. Compute for cell number per milliliter using the formula: Cell count ðcells=mlÞ ¼ ½Total number of cells=Dilution Factor
10, 000 12. For efficient protoplast transfection, a cell count of 2
106 is required. Adjust the final concentration with MMG buffer. These steps are illustrated in Fig. 1. 3.3 Protoplast Transfection

1. The amount of plasmid DNA to be used in transfection should be 10–20 mg per reaction, depending on the type of experiment (see Note 9). To do this, grow the clones in 50 ml growth medium with the appropriate amount of antibiotics. Isolate the plasmid using medium- or large-scale isolation kit (see Note 10). 2. In a 15 ml round-bottom polypropylene tube, place 200 μl protoplasts and then add 5–10 mg of plasmid DNA and immediately mix by swirling the tube gently. Add 110 μl PEG-calcium transfection solution (see Note 11) buffer, and mix by gently swirling the tube until the mixture is homogeneous. 3. Incubate for 20 min at room temperature. 4. Stop the reaction by adding 440 μl of W5 buffer. 5. Collect the protoplasts by spinning at 800 rpm for 3 min at 25  C (deceleration off). 6. Re-suspend in W1 buffer. 7. Incubate for 16 h at 28  C in the dark to allow the expression of the introduced constructs. 8. After 16 h, view cells with a fluorescence microscope with the appropriate excitation and emission wavelengths and filters for the fluorescent proteins used. 9. Acquire and process images using imaging software. An example of transfection results with a fluorescent reporter is shown in Fig. 2.

Rice Protoplast Isolation and Transfection

8-11 day old rice seedlings

Collect protoplasts by filtering (0.45μm), wash twice with 10 ml W5 buffer. Centrifuge at 100 x g 5 mins. 28°C , deceleration turned OFF, re-suspend in 5 ml MMG buffer

50 seedlings

321

Cut both stem and leaf sheath using a fresh razor blade

Submerge tissues in 10 ml protoplast isolation buffer, vacuum-infiltrate for 30 mins. Incubate at RT for 4-5 hours

Dilute 5X, load 9 μl onto a hemocytometer, count the total cells. Determine cell concentration using the formula: Cells/ml = total cells counted X (DF/number of squares) X 10,000 Fig. 1 A diagram of the steps involved in rice protoplast isolation is shown. The procedure yields protoplast preparations that are useful for transfection and reporter gene assays

4

Notes 1. Murashige and Skoog basal medium was used in the study to save time and to reduce errors in reagent preparation. One can opt to prepare MS medium from its individual components if desired.

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Untransfected (MMG buffer)

Transfected, no YFP plasmid

Transfected with YFP plasmid

Brightfield (400X)

UV Filter (400X)

YFP Filter (400X)

Bar = 10 µm

Fig. 2 Expression of yellow fluorescent protein (YFP) in transfected etiolated rice protoplasts. The protoplasts were viewed using an Olympus BX50 fluorescence microscope, and the images were acquired and processed using the Olympus cellSens imaging software. YFP fluorescence was excited at 514 nm and detected at 590 nm with UV and YFP filter sets. A 10 μM scale bar is shown in the lower right panel

2. 250 ml of growth medium is sufficient to grow 50 rice seedlings, which is more than enough to obtain 2
106 cells/ml. 3. Cell wall digesting enzymes Cellulase Onozuka R10 or RS and Macerozyme R10 were obtained from Yakult Honsha, Ltd. Japan (https://www.yakult.co.jp/ypi/en/product.html). This brand yielded the most efficient protoplast isolation compared to other brands tested. Other protocols also suggested using enzymes from this manufacturer. 4. Important: Use PEG4000 Cat. No. 81240 from SigmaAldrich [6]. 5. For experiments involving fluorescence microscopy, using etiolated protoplasts will ensure that no chlorophyll signal will interfere with the fluorescent signal.

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6. After digestion, rice leaf sheath and stems will not readily disintegrate compared to dicots. The tissues will be softened but are still intact. After the first wash, adding W5 buffer and slightly pressing on the tissues using a stirring rod or spatula will release more protoplasts. 7. Centrifugation must be done with a swinging bucket rotor to reduce damage to the protoplasts during collection. 8. Optimally, the protoplasts should be transfected immediately after isolation, but if this is not possible, they can be stored at 4  C overnight for use the next day. Some of the stored protoplasts are still viable after 24 h, but many may exhibit damage reducing the number of viable cells. 9. The amount of plasmid DNA depends on the type of experiment being done. For example, a transactivation assay involving co-transfection of two plasmids will require 2
amount of effector plasmid to reporter plasmid. It is important to consider the type of experiment when deciding on the amount of DNA to be added. 10. A medium-scale commercial plasmid isolation kit typically provides sufficient DNA for a transfection experiment. 11. A 40% PEG concentration in the PEG-calcium transfection buffer is typically the most efficient for high levels of transfection, but a high concentration of PEG also damages the protoplasts, so testing a range of PEG concentrations may be necessary to determine the level of PEG that is optimal in a particular assay. References 1. Cocking EC (1960) A method for the isolation of plant protoplasts and vacuoles. Nature 187:927–929 2. Sheen J (2001) Signal transduction in maize and Arabidopsis mesophyll protoplasts. Plant Physiol 127:1466–1475 3. Potrykus I, Shillito RD, Saul M, Paszkowski J (1985) Direct gene transfer: state of the art and future perspectives. Plant Mol Biol Rep 3:117–128 4. Fromm M, Taylor LP, Walbot V (1985) Expression of genes transferred into monocot and dicot plant cells by electroporation. Proc Natl Acad Sci U S A 82:5824–5828 5. Hillmer S, Gilroy S, Jones R (1992) Visualizing enzyme secretion from individual barley (Hordeum vulgare) aleurone protoplasts. Plant Physiol 102:279–286 6. Yoo SD, Cho YH, Sheen J (2007) Arabidopsis mesophyll protoplasts: a versatile cell system

for transient gene expression analysis. Nat Protoc 2(7):1565–1572 7. Chen S, Tao L, Zeng L, Vega-Sanchez ME, Umemura K, Wang GL (2006) A highly efficient transient protoplast system for analyzing defense gene expression and protein-protein interactions in rice. Mol Plant Pathol 7 (5):417–427 8. De Sutter V, Vanderhaeghen R, Tilleman S, Lammertyn F, Vanhoutte I, Karimi M, Inze D, Goossens A, Hilson P (2005) Exploration of jasmonate signaling via automated and standardized transient expression assays in tobacco cells. Plant J 44:1065–1076 9. Kapila J, De Rycke R, Van Montagu M, Angenon G (1997) An Agrobacterium-mediated transient gene expression system for intact leaves. Plant Sci 122:101–108 10. Worley CK, Zenser N, Ramos J, Rouse D, Leyser O, Theologis A, Callis J (2000)

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Degradation of Aux/IAA proteins is essential for normal auxin signaling. Plant J 21:553–563 11. Wang S, Tiwari SB, Hagen G, Guilfoyle TJ (2005) Auxin-response factor 7 restores the expression of auxin-responsive genes in mutant Arabidopsis leaf mesophyll protoplasts. Plant Cell 17:1979–1993 12. Kovtun Y, Chiu WL, Tena G, Sheen J (2000) Functional analysis of oxidative stress-activated mitogen-activated protein kinase cascade in plants. Proc Natl Acad Sci U S A 97:2940–2945 13. Tena G, Asai T, Chiu WL, Sheen J (2001) Plant mitogen-activated protein kinase signaling cascades. Curr Opin Plant Biol 4:392–400

14. Hwang I, Sheen J (2001) Two-component circuitry in Arabidopsis cytokinin signal transduction. Nature 413:383–389 15. Sheen J (1996) Ca2+-dependent protein kinases and stress signal transduction in plants. Science 274:1900–1902 16. Zhang Y, Su J, Duan S, Ao Y, Dai J, Liu J, Wang P, Li Y, Liu B, Feng D, Wang J, Wang H (2011) A highly efficient rice green tissue protoplast system for transient gene expression and studying light/chloroplast-related processes. Plant Methods 7:30–43 17. Dixit S, Biswal AK, Min A et al (2015) Action of multiple intra-QTL genes concerted around a co-localized transcription factor underpins a large effect QTL. Sci Rep 5:15183

Chapter 22 Identification and Downstream Analyses of Domains Amplified in Plant Genomes: The Case of StAR-Related Lipid Transfer (START) Domains in Rice Sanjeet Kumar Mahtha, Ravi Kiran Purama, Renu Kumari, and Gitanjali Yadav Abstract Plant genomes can withstand small- and large-scale duplications, at a far greater success than any other kingdom in the tree of life, resulting in the existence and evolution of gene families, often with over a hundred members! The gene families, in turn, go through subfunctionalization or neofunctionalization, to form protein domains performing unique or grouped functions in context of the original activity. Due to the large number of such cases in the plant kingdom, it has become a routine task for plant biologists to investigate their specific gene family of interest. In this chapter, we provide a simple and standard pipeline for this effort, taking the example of steroidogenic acute regulatory protein (StAR) related lipid transfer (START) domains in rice, as reference. We describe the extraction, processing, and downstream analysis of Oryza sativa var. japonica proteome towards identification and comparative exploration of START domains. This was done by training profile Hidden Markov Models (HMM) of 35 reported START domains in Arabidopsis, which were then used to search potential homologs in rice. Downstream investigations included domain structure analysis, visualization of exon–intron patterns, chromosomal localization of START genes, and phylogenetic studies, followed by identification of cis-regulatory elements and gene regulatory network construction. Additionally, we have also highlighted various alternative tools and techniques that can be used to perform similar analyses, along with salient features. Key words Proteome analysis, Hidden Markov Models, Phylogenetics, START domains, Transcription factors, Oryza

1

Introduction Technological innovations in genomics and proteomics have helped to generate very large biological datasets in very short time spans, and this has led to great advancement in the field of computational biology and bioinformatics [1, 2]. Some of these advances have pioneered the assembly of millions of short DNA reads generated through next generation sequencing technologies,

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into supercontigs or pseudo molecules which in turn are structurally annotated for genes and functionally annotated through homology with other reference genomes [3]. These methods are able to successfully identify gene families, a feature quite common to plant genomes, due to duplications and subsequent evolution; but functional annotation of individual members or subsets within these gene families, is a completely different task, and often requires experimental verification and biological information, both of which may take a lot of time. In this work, we present some basic computational tools to perform identification and downstream analysis of gene/protein sequences in the Oryza genome. As a model, we have used the steroidogenic acute regulatory protein (StAR) related lipid transfer (START) domains to demonstrate application of the selected computational biology tools. In brief, START domains are relatively small evolutionarily conserved domains of approximately 210 amino acids, that were initially identified as the lipid-binding domain in mammals [4], and later shown to be significantly amplified in the plant kingdom with Arabidopsis having 35 START domains and rice 29 (together in Japonica and Indica homologs), compared to human and mice both of which have 15 START domains in each [5, 6]. These domains belong to the SRPBCC (START/RHO_alpha_C/ PITP/Bet_v1/CoxG/CalC) superfamily in the NCBI Conserved Domains Database, named after six major subfamilies that possess the typical α/β helix-grip conformational fold [7, 8]. START domain containing proteins vary in both size and domain structure, and are also reported from protists and bacteria [9]. START domains have been shown to play a crucial role in the transfer of lipids/sterols, lipid signaling, and modulation of transcription activity in plants [7, 10]. We begin with the full genome and proteome of a species of interest, in this case, Oryza sativa var. japonica and we proceed to identify and perform a comprehensive comparative genomics investigation of a family of interest (in this case, the START domains), in our genome. We begin with the assumption that prior information may not be available for our family of interest and we initiate the study by performing homology-based identification and validation using computational methods. We then perform sequence and structural analyses on the gene and protein sequences as well as cis-regulatory elements analysis of the upstream regions of START genes. The entire set of methods can be undertaken and replicated for any gene of interest in any species of interest, and the tools presented here are not exhaustive, but rather very selective based on ease of use, and popularity in the community.

Identification and Downstream Analyses of Domains Amplified in Plant. . .

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Materials (Data Collection) There are a number of online resources for protein sequences, including Uniprot [11], NCBI RefSeq [12], Protein Information Resource (PIR) [13], Swiss-prot [14], and Interpro [15]. Complete proteome/genome sequences can be obtained from respective organism databases such as TAIR (https://www.arabidopsis.org) [16] for Arabidopsis or RGAP (http://rice.plantbiology.msu. edu/) [17] for rice. In addition repositories like the Ensembl (https://www.ensembl.org) [18] or Phytozome (https:// phytozome.jgi.doe.gov/pz/portal.html) [19], are hubs for accessing and analyzing large genomic datasets for multiple species. In this study, the proteome, genome, and annotations for Oryza sativa var. japonica were downloaded from phytozome v12 [19]. The known sequences of 35 START domain proteins of Arabidopsis were retrieved from the NCBI GenBank [20] and the START domain regions were extracted from these proteins based on their annotated border residues represented in literature [5].

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Methodology and Results All tools/techniques demonstrated below have been used with default parameters unless specified. An illustrative workflow for the methodology is given in Fig. 1. In each section below, we have provided an overview of available tools in the public domain,

Fig. 1 A schematic workflow used in this chapter for identification and downstream analysis of START domains in Oryza sativa var. japonica

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followed by a description of the tools used in this study for the family and genome of intertest, ending with self explanatory results and figures for each tool used. 3.1 Identification of START Homologs in Rice Proteome

Several computational tools are available to perform homology based identification of proteins including direct match methods like BLASTP (proteins) and BLASTX (using DNA/RNA as query), [21] or profile based methods as in case of HMMER, phmmer, jackhmmer, hmmscan that can be used against sets of protein sequences or profile databases [22]. Profile Hidden Markov Models (HMM) for known START domain sequences from Arabidopsis were used for searching putative START domains across the proteome data of Oryza sativa var. japonica. HMM profiles were constructed using HMMER 3.1b1 (http://hmmer.org/) [23]. The hits obtained in rice were filtered in order to remove the false positives at a set cutoff of minimum 80 amino acids considering the necessity of a minimum domain length based on biological information (Hits obtained